#dorleco

Introduction:-

If you’ve been half-thinking about switching to an electric car but you’re not quite ready to commit, PHEVs are probably the most sensible middle ground on the market right now. They give you the clean, quiet experience of electric driving for most of your everyday journeys — without the range anxiety that still puts some people off going fully electric. But “plug-in hybrid” gets thrown around a lot, and there’s a fair bit of confusion about what these cars actually do under the bonnet. So let’s get into it properly.

What exactly is a PHEV, and how is it different from a normal hybrid?

A PHEV has two powertrains working in parallel: a conventional combustion engine (petrol or diesel) and an electric motor powered by a rechargeable battery pack. The crucial difference from a standard hybrid is that you can plug it in.

Standard hybrids — like the original Toyota Prius — do combine an engine and an electric motor, but their batteries are quite small and can only recharge themselves through the engine and regenerative braking. You can never get more than a mile or two of pure electric driving out of them. PHEVs carry significantly larger batteries, typically between 8 and 25+ kWh, and that changes everything. Plug one in overnight at home, and you’ll have enough charge for your entire daily commute on electricity alone — no petrol burned at all. The combustion engine only wakes up when the battery gets low or when you specifically need extra power for motorway overtaking or heavy loads.

How does a PHEV actually work? Series vs. parallel explained

Most people buy a PHEV without ever knowing there are two fundamentally different ways they can be configured. It matters more than you’d think, because it affects how the car drives and how efficient it is in different conditions.

Parallel PHEV

Both the electric motor and the combustion engine are mechanically connected to the wheels. They can work independently or together. Most efficient at highway speeds, where the engine is in its sweet spot. Common in the Toyota Prius Plug-in and Kia Sorento PHEV.

Series PHEV

Only the electric motor drives the wheels. The combustion engine runs as a generator to top up the battery when needed. Feels like driving a full EV. Very smooth and efficient in city stop-start traffic. Common in: Chevrolet Volt, BMW i3 REx (older). Many modern PHEVs—like certain Mitsubishi and Honda models—are smart enough to switch between both modes automatically based on your speed, battery level, and how hard you’re pushing the accelerator. The vehicle control software manages all of this in real time, which is where a lot of the engineering complexity lives.

What does a PHEV actually consist of? Key components

The reason PHEVs are more expensive than standard hybrids comes down to how much hardware they’re packing. Here’s what’s inside:

The battery pack

This is the heart of the PHEV experience. A larger, higher-capacity lithium-ion battery pack (usually mounted low in the floor for weight distribution) is what gives you that usable electric range. Protect the battery through regular charging and moderate charge cycles, and it should last the life of the car.

The electric motor

Handles propulsion during electric-only mode and assists the combustion engine under heavy load. Electric motors deliver peak torque instantly from zero rpm, which is why PHEVs often feel surprisingly punchy off the line compared to same-sized petrol cars.

The power electronics and VCU

This is where companies like Dorleco live. The Vehicle Control Unit (VCU) is the electronic brain—it's constantly monitoring battery state, throttle position, vehicle speed, regenerative braking opportunity, and cabin loads to decide in real time which power source to draw from. Get this calibration right and you get a seamlessly smooth, efficient car. Get it wrong and you get jerky transitions and wasted energy. Dorleco’s evCode software and ToughCase VCU range are purpose-built for exactly this kind of PHEV and EV powertrain control.

The combustion engine

Usually a smaller, more fuel-efficient engine than you’d find in a comparable non-hybrid. It’s optimized to run in its most efficient rev range when it does operate, reducing fuel consumption compared to a traditional car where the engine is doing all the work all the time.

How do you charge a PHEV, and how long does it take?

This is one of the things that makes PHEVs more approachable than full EVs for a lot of people. You don’t need a dedicated home charging station to own one, though it helps.

PHEV Charging Options at a GlanceCharger TypeVoltageApprox. Charge TimeBest ForStandard wall socket (Level 1)120V5–6 hours Overnight home charging Home wallbox (Level 2) 240V, 1–3 hours Faster overnight or daytime top-up Public AC charging (240V, 1–3 hours) Workplace or retail charging Regenerative braking N/A Continuous (partial) Recovers energy while driving

The nice thing about a Level 1 standard socket is that it’s really just like charging your phone—you plug in before bed, and by morning you’re ready for a full electric commute. Most people with predictable daily mileage under 40 miles will never actually need to use the petrol engine on weekdays.

Are PHEVs actually good for the environment?

When you charge a PHEV regularly and do most of your driving on electric power, the environmental case is strong. City driving on pure electric means zero tailpipe emissions exactly where air quality matters most. Studies show that a regularly charged PHEV can cut CO₂ emissions by 30 to 70% compared to the equivalent petrol car — that’s a genuine, meaningful impact.

PHEV vs. full BEV: Which makes more sense right now?

This is the real question for most buyers. Here’s the honest comparison:

PHEV vs. BEV: Head-to-Head Factor | PHEV BEV (Full EV) Daily electric range: 20–60 miles, 150–400+ miles No range anxiety on long trips Yes (petrol backup) Growing (more chargers) Home charging needed Helpful but not critical Strongly recommended CO₂ reduction potential: 30–70% (if charged) Up to 100% on renewables Upfront cost: higher than regular hybrid Generally higher tax incentives Up to $7,500 in US Up to $7,500 in USMechanical complexity Higher (two powertrains) Lower (fewer moving parts)

The bottom line: if you have a predictable daily commute under 40 miles, somewhere to charge at home or work, and you regularly do longer trips that would stress range anxiety on a full EV, a PHEV makes a lot of sense. If you do mostly city driving and have reliable home charging, a full BEV is probably the cleaner, lower-maintenance choice in the long run. Dorleco covers BEV powertrain control extensively — if you’re comparing both paths from an engineering perspective, our BEVs vs. PHEVs deep-dive is worth a read.

Where do PHEVs fit in the EV transition—and what’s Dorleco’s role?

PHEVs aren’t the end destination. They’re a bridge and a genuinely useful one. For the millions of households that can’t yet afford a full BEV, don’t have easy home charging access, or regularly need long-range capability, PHEVs deliver most of the day-to-day environmental benefit with far less inconvenience. At Dorleco, we build the control systems that sit at the heart of these vehicles. Our Vehicle Control Units manage the real-time handoffs between electric and combustion power, our evCode software platform handles powertrain logic and energy management, and our Controls Software & Development team works directly with OEMs and Tier 1 suppliers to engineer the systems that make PHEVs—and full EVs—actually perform as promised. If you’re working on a PHEV or BEV project and need engineering support, get in touch — that’s exactly what we do.

So, is a PHEV worth it?

Introduction

A battery management system (BMS) is the electronic brain of a rechargeable battery pack. It continuously monitors cell voltage, temperature, and current, then uses that data to keep the battery safe, balanced, and healthy. In electric vehicles, the BMS prevents overcharging, manages heat, estimates range, and communicates with the rest of the vehicle — all in real time.

In This Guide

What is a Battery Management System?

Why EVs Can’t Function Without a BMS

How a BMS Actually Works

The 6 Core Components of a BMS

Key Functions: SOC, SOH, Balancing & More

Real-World BMS Design Challenges

Where BMS Technology Is Heading

Frequently Asked Questions

What Is a Battery Management System (BMS)?

If you’ve ever wondered what actually keeps an electric vehicle battery from catching fire, losing range, or dying prematurely — that’s the BMS’s job. And it’s a surprisingly complex one.

A battery management system is the electronic system responsible for monitoring and controlling a rechargeable battery pack. At its core, it’s doing three things simultaneously: watching what’s happening inside the battery, deciding whether it’s safe to keep operating, and taking action when it isn’t.

You’ll find BMS technology everywhere batteries are used at scale — electric cars, hybrid vehicles, grid energy storage, power tools, aerospace systems, and medical devices. But the most demanding and highest-stakes application by far is in EVs, where battery packs can hold hundreds of kilowatt-hours of energy and cost tens of thousands of dollars to replace.

Why EVs Literally Can’t Function Without a BMS

An EV battery pack isn’t one big battery — it’s hundreds or thousands of individual lithium cells connected in series and parallel. And here’s the problem: no two cells are identical. They have slightly different capacities, internal resistances, and aging rates. Left unmanaged, these differences compound over time into serious problems.

The stakes are high. A single overcharged cell can trigger thermal runaway — a chain reaction where one cell’s heat causes neighboring cells to overheat, potentially resulting in fire. The BMS is the primary defense against this happening.

More specifically, a well-designed BMS does four critical things for an EV:

Safety

Prevents Dangerous Failures: Stops short circuits, overcharging, over-discharging, and temperature extremes before they cause damage or fire.

Longevity

Extends Battery Life Keeps cells operating within their ideal voltage and temperature ranges, slowing degradation and maximizing useful lifespan.

Performance

Maximizes Range Ensures the full capacity of the pack is usable by keeping cells balanced, so you’re not limited by the weakest cell.

Intelligence

Enables Smart Decisions Feeds real-time data to the vehicle’s VCU so regenerative braking, power delivery, and charging can all be optimized.

How a BMS Actually Works — Step by Step

At a high level, a BMS is a sense-process-act loop running continuously. Here’s how that plays out in practice:

StepWhat HappensKey Parameters1. Data CollectionSensors measure conditions across every cell in the pack, multiple times per second.Voltage, temperature, current2. ProcessingThe MCU runs algorithms to calculate derived states like SOC and SOH from the raw sensor data.SOC, SOH, cell balance delta3. Decision MakingThe BMS compares current conditions against pre-defined safe operating limits and decides what action (if any) is needed.Voltage thresholds, temperature limits, current caps4. ActionCommands are sent to cooling systems, balancing circuits, charge controllers, or the VCU to maintain safe conditions.Cooling, balancing, shutdown signals5. CommunicationAll status data is broadcast to other vehicle systems so they can coordinate around battery limits in real time.CAN bus messages, fault codes

The entire loop happens fast — typically every few milliseconds for critical protections like overcurrent and every few seconds for slower parameters like SOH estimation. The speed and accuracy of this cycle directly determine how safe and efficient the battery system is.

The 6 Core Components of a Battery Management System

A BMS isn’t a single chip — it’s an integrated system of hardware and software working together. These are the main building blocks:

1. Cell Voltage Monitoring Circuit

This is perhaps the most fundamental part of any Battery Management System. It measures the voltage of each individual cell, usually with millivolt-level accuracy. Why does that matter? Because the line between a healthy lithium cell and a dangerous one can be as thin as a few hundred millivolts. Catching a cell drifting toward its limits — in either direction — is the first line of defense.

2. Cell Balancing Circuit

Over time, cells in a pack develop slightly different charge levels. The balancing circuit’s job is to equalize them. There are two approaches: passive balancing (burning off excess charge from higher cells as heat — simpler but wasteful) and active balancing (redistributing charge from higher cells to lower ones — more efficient but more complex). Higher-end EV systems increasingly use active balancing to maximize usable range.

3. Temperature Sensors

Lithium cells have a Goldilocks zone — typically 15°C to 35°C for optimal performance. Too cold and they lose capacity and can be damaged by charging. Too hot and degradation accelerates dramatically, and thermal runaway risk increases. Thermistors placed throughout the pack give the BMS the thermal map it needs to act before temperatures become dangerous.

4. Current Sensors

Current sensors track how much charge is flowing in and out of the pack. This is essential for SOC estimation (Coulomb counting requires knowing exactly how much current has flowed over time) and for detecting overcurrent conditions that could damage cells or wiring. High-precision hall-effect sensors are common in automotive applications.

5. Microcontroller Unit (MCU)

The MCU is where all the intelligence lives. It runs the BMS algorithms — SOC estimation, SOH tracking, balancing decisions, and fault detection — and sends commands out to protective circuits and communication interfaces. In safety-critical automotive applications, the MCU typically runs on an ASIL-rated processor (ISO 26262 functional safety standard) with redundant watchdog circuits.

6. Communication Interface

A BMS doesn’t work in isolation. It needs to share data with the Vehicle Control Unit (VCU), the charger, the dashboard, and, in modern EVs, potentially the cloud. The dominant protocol in automotive is CAN bus, though some systems also use LIN for secondary sensors or higher-bandwidth options like CAN FD and Automotive Ethernet for data-heavy BMS architectures.

The Key Functions a BMS Performs Every Second

State of Charge (SOC) Estimation

SOC is the battery equivalent of a fuel gauge — it tells you what percentage of the pack’s capacity is currently available. But unlike a fuel gauge, it can’t be measured directly. The Battery Management System estimates it using methods like Coulomb counting (integrating current over time), open-circuit voltage (OCV) measurement, or, increasingly, model-based filtering approaches like the Extended Kalman Filter. Temperature, aging, and cell-to-cell variation all complicate this estimate, which is why accurate SOC is genuinely hard to achieve.

Real-time metric

State of Charge (SOC)

Current charge level as % of capacity. Changes continuously. Drives range estimation and charging decisions. Analogous to a fuel gauge.

Long-term metric

State of Health (SOH)

How much of the original capacity remains after aging? Changes slowly over months. Drives maintenance decisions and battery replacement timing.

State of Health (SOH) Monitoring

Where SOC tells you how full the tank is right now, SOH tells you how big the tank has gotten over time. As cells age, they lose capacity — a battery that held 100 kWh when new might only hold 80 kWh after a few years of heavy use. The BMS tracks this degradation by monitoring capacity fade, internal resistance growth, and cycle count. This data matters for warranty programs, second-life applications, and long-term fleet planning.

Cell Balancing

Even cells that started identical will drift apart over time. A pack where one cell is at 20% SOC while the rest are at 50% can only be discharged to 0% on that weakest cell — effectively losing usable capacity from every other cell. Regular balancing prevents this drift from compounding. It’s one of those invisible functions that, when done well, quietly extends the pack’s useful life by years.

Thermal Management

Heat is the enemy of battery longevity. The BMS monitors temperatures across the pack and actively manages them — commanding cooling fans, liquid cooling loops, or heating elements as needed. In high-performance EVs and fast-charging applications, sophisticated thermal management isn’t optional. A pack that consistently runs 10°C hotter than optimal can lose years of service life.

Overcharge and Over-Discharge Protection

This is the BMS’s most critical safety function. Charging a lithium cell beyond its maximum voltage causes chemical changes that can lead to thermal runaway. Discharging below the minimum voltage causes irreversible capacity loss and copper plating of the anode, which creates internal short-circuit risks. The BMS monitors these limits continuously and will interrupt charging or discharging before a cell crosses a dangerous threshold.

Diagnostics and Fault Logging

Modern BMS units don’t just react to problems — they log data over time. Temperature trends, voltage deviations, charge cycle counts, and fault events are recorded and made available for fleet management systems, service technicians, and cloud analytics platforms. This diagnostic trail is invaluable for warranty analysis, predictive maintenance, and ongoing battery optimization.

Chemistry Diversity NMC, LFP, NCA, LTO — each lithium chemistry has different voltage windows, charge curves, and thermal behaviors. A BMS tuned for one chemistry will perform poorly or fail dangerously with another. Multi-chemistry support requires either separate firmware profiles or adaptive algorithms.

Environmental ExtremesAn EV BMS must work reliably from −40°C in a Scandinavian winter to +85°C in a Middle Eastern summer, while surviving vibration, humidity, and EMI from motor inverters. Automotive-grade validation is significantly more demanding than consumer electronics.

SOC/SOH Accuracy Under Real-World ConditionsCoulomb counting drifts over time. OCV measurement requires the battery to be at rest. Model-based approaches need accurate cell models that themselves age. Getting SOC error below 2–3% consistently across temperature and aging states is a genuine engineering challenge.

Cost vs. Performance Trade-offsPremium sensors, high-frequency sampling, and sophisticated balancing circuits add cost. At the volume of automotive production, every dollar matters. BMS designers constantly balance measurement resolution against bill-of-materials cost.

Functional Safety ComplianceAutomotive BMS development increasingly requires ISO 26262 compliance (up to ASIL-C or ASIL-D for critical safety functions). This means formal hazard analysis, redundant monitoring paths, and exhaustive verification and validation — all of which add significant development cost and time.

Where BMS Technology Is Heading

The BMS of 2030 will look meaningfully different from what’s in most EVs today. A few trends are shaping the direction:

AI-Powered Estimation

Machine learning models that learn individual cell aging patterns can estimate SOC and SOH more accurately than physics-based models alone, especially as cells age in unexpected ways.

Cloud Connectivity & OTA

BMS firmware updates delivered over-the-air means algorithms can be improved after delivery. Cloud connectivity also enables fleet-level battery health analytics that individual vehicles can’t achieve alone.

Solid-State Battery Support

Solid-state cells have fundamentally different electrochemical characteristics. Next-gen BMS hardware and algorithms will need to be redesigned to manage them optimally.

Digital Twin Integration

Real-time digital twins of the battery pack running alongside the physical BMS enable predictive failure detection and more aggressive optimization without compromising safety margins.

V2G & Bidirectional Charging

Vehicle-to-grid systems demand BMS architectures that can manage complex bidirectional energy flows while protecting battery health — a very different operating profile from simple charge-discharge cycles.

Cell-Level Intelligence

Distributed BMS architectures with intelligence at the cell level (rather than centralized) reduce wiring complexity and enable faster, more precise response to individual cell events.

Building an EV System That Needs BMS Integration?

Dorleco’s engineering team works on BMS integration, VCU development, and full-stack EV controls — from architecture to validation. Let’s talk about your project.

Advantages

Enhanced Safety: Continuously guards against overcharging, over-discharging, short circuits, and thermal runaway — the BMS is your battery’s last line of electronic defense.

Longer Battery Life: By keeping every cell within its ideal operating window, a BMS dramatically slows capacity fade. A well-managed pack can outlast an unmanaged one by years.

Accurate Range Estimation: Reliable SOC estimation means the range indicator on your dashboard is actually trustworthy — no sudden “range drops” that catch you off guard.

Maximized Usable Capacity: Cell balancing ensures you’re using the full capacity of the pack, not just whatever the weakest cell will allow.

Real-Time Fault Detection: The BMS logs and flags anomalies — unusual temperature spikes, cell voltage deviations — before they become failures, enabling proactive maintenance.

Optimized Charging: The BMS coordinates with the charger to apply the ideal charge profile for the battery’s current state, temperature, and age — protecting cells while minimizing charge time.

Seamless Vehicle Integration: Via CAN bus, the BMS feeds real-time battery data to the VCU, enabling intelligent power management, regenerative braking optimization, and driver information.

Regulatory Compliance: In automotive applications, a certified BMS therefore helps manufacturers meet safety standards like ISO 26262, UL 9540, and UN ECE R100.

Disadvantages

Added Cost: A high-quality automotive BMS with precision sensors, active balancing, and safety-rated processors isn’t cheap. It adds meaningful cost to the battery system — especially at smaller production volumes.

Design Complexity: Building a BMS that works reliably across all operating conditions requires deep expertise in battery electrochemistry, embedded firmware, functional safety, and thermal engineering — all simultaneously.

SOC/SOH Estimation Errors: Despite sophisticated algorithms, real-world estimation accuracy is still imperfect — particularly in extreme temperatures or with heavily aged cells. This can cause range anxiety or premature maintenance alerts.

Parasitic Power Draw: The BMS itself consumes a small but continuous amount of power — even when the vehicle is parked. Over extended storage periods, this can slowly drain the pack.

Single Point of Failure Risk: If the BMS malfunctions, it can incorrectly shut down a healthy battery, trigger false alarms, or — in a worst case — fail to protect against a genuine fault. Redundancy and rigorous validation are essential.

Chemistry Lock-in: A BMS tuned for one battery chemistry (e.g., NMC) won’t work optimally out-of-the-box with another (e.g., LFP). Multi-chemistry support requires additional engineering effort.

Validation Overhead: Automotive-grade BMS certification (ISO 26262, ASPICE) therefore demands exhaustive testing and documentation, which in turn adds significant time and cost to development programs.

Conclusion

The Battery Management System is, without question, one of the most important pieces of technology in the electric vehicle ecosystem — and one of the least visible to the people who depend on it most. Every time you charge your EV overnight, push it hard on the highway, or rely on its range estimate to get you home, the BMS is quietly doing its job in the background.

As battery technology continues to evolve — toward higher energy densities, faster charging, solid-state chemistries, and bidirectional grid integration — the Battery Management System will need to evolve right alongside it. The systems going into vehicles today are already far more capable than what was state-of-the-art five years ago. The BMS platforms of 2030 will be smarter still, incorporating AI-driven estimation, cloud connectivity, and cell-level intelligence that we’re only beginning to develop.

Introduction

The phrase “bespoke controls” refers to control systems that are created, developed, and implemented especially to satisfy particular operational needs. Bespoke controls, as opposed to off-the-shelf control panels or interfaces, are customized for the user-system combination, taking into account the environment, legacy systems, user experience, and specific process flows.

From smart homes to scientific instrumentation, from industrial automation to aerospace, custom controls allow for performance and flexibility that generic systems frequently cannot. The customized approach is becoming more and more important as operations get more complicated and demands get more precise.

The Reasons Behind the Rise in Bespoke Controls

Interest in custom control systems is being fueled by several factors across industries:

Enhanced process complexity:

Real-time data, sophisticated sensors, integrated automation, and many user roles are all part of contemporary manufacturing, smart-home interfaces, and aerospace systems. The entire end-to-end workflow might not be supported by off-the-shelf solutions.

Legacy integration and digital transformation:

Many facilities need to integrate enterprise systems (MES/SCADA/ERP) or new controls with older equipment. The capacity to connect the old and the new is provided by bespoke controls. Custom machine control systems, for instance, “deliver exceptional reliability, scalability, and long-term productivity” in industrial automation, according to a recent article.

Demands for performance, safety, and regulations:

Safety, dependability, and compliance are crucial in industries like critical infrastructure, medical devices, aerospace, and defense. Tighter conformance to standards is made possible by custom controls.

Operational and competitive differentiation:

Companies now see control systems as a strategic asset that facilitates optimization, improved user experience, and quicker change response rather of just as a way to “make something work.”

Energy and sustainability pressures :

Pressures related to sustainability and energy Systems that are precisely adjusted for load, cycle, and user behavior can result in reduced lifecycle costs, increased efficiency, and energy savings. Customized performance and energy efficiency, for instance, have been demonstrated to be advantageous for air-handling devices.

These factors make the case for custom controls strong, particularly when they are in line with long-term planning as opposed to only short-term requirements.

Principal Advantages of Customized Controls

The following are the main benefits of implementing custom control systems:

Customized to Meet Particular Needs

The system can precisely handle the user’s functional needs, operational environment, and workflow because it was created for a specific application. “The control panel is built to your site, application, and environmental needs,” according to one source.

Enhanced Efficiency & Performance

Custom controls allow you to remove features that aren’t needed, optimize the hardware/software interaction, streamline the user interface, and make sure the system functions as intended. Custom control systems have been shown to increase productivity, decrease bottlenecks, and improve uptime in industrial automation.

Better Interface & User Experience

Operators may interact with the system intuitively thanks to custom-built interfaces, which decrease errors, expedite training, and enhance usability. This is a crucial distinction, especially in industries like consumer systems, smart homes, and medical devices.

Smooth Interaction with Current Systems

Integrating with historical equipment, current networks, or business systems is one of the main challenges when implementing controls. Compatibility considerations, required interfaces, and seamless integration can all be incorporated into a custom design. Control panel experts, for instance, place a strong emphasis on design with regard to legacy equipment and “space, layout, IP ratings, and power supply.”

Flexibility and Scalability

Bespoke controls make it easier to grow or modify the system as operational demands change (for example, manufacturing volume rises, new modules are added, or new regulations are introduced). Instead of being constrained by the limitations of an off-the-shelf product, custom systems can be constructed with flexibility, modular architecture, and upgrade routes in mind.

Improved Compliance, Safety, and Reliability

Bespoke controls enable you to precisely incorporate the necessary certifications, safety logic, redundancy, fault-tolerance, and monitoring for situations with high safety or compliance demands (such as aerospace, defense, and critical infrastructure). Compared to generic systems, this can provide a better level of confidence.

Cost-Effectiveness Over Time

Bespoke controls may be more expensive to build initially, but they can save a lot of money over time in the form of fewer changes, less downtime, less training, improved workflow fit, increased productivity, and eventually a higher return on investment. Long-term savings from less vendor dependence and training are highlighted by certain custom software sources.

Differentiation and Competitive Advantage

A customized control system can be a differentiator in a variety of industries. A competitive edge might be supported by tighter integration, better user experience, faster response, or cheaper operational costs. This is particularly true when the value-proposition includes the control system (e.g., advanced manufacturing, OEM machinery, smart home automation).

Trade-offs and Considerations

It’s critical to acknowledge that custom controls have limitations. Here are a few common difficulties:

Higher initial investment :

Increased upfront costs are a result of engineering, development, testing, and bespoke hardware.

Longer development time and lead-time :

Lead time and development time are longer for custom designs than for off-the-shelf products.

Dependency on vendors and support:

Long-term support, upgrades, and documentation may become problems if the system is developed by an internal team or a small business.

Risk of over-engineering :

Adding more complexity than is necessary carries a risk. Higher costs, less frequent maintenance, and possible brittleness can result from that.

Problems with standardization and integration:

Although bespoke controls are meant to be integrated, they could complicate future upgrades or tie the system into a proprietary ecosystem if they are not carefully built.

Risk of obsolescence and maintenance:

Upkeep may become challenging if the original designer quits or if documentation is inadequate. Additionally, custom systems may become outdated more quickly than standard ones due to the rapid advancement of technology.

Decreased leverage for vendor/market innovation:

Off-the-shelf solutions enjoy the advantages of frequent upgrades, extensive user testing, and economies of scale. Custom systems might not have that scope.

Comparative Table: Bespoke vs Off-the-Shelf Controls

FeatureBespoke ControlsOff-the-Shelf ControlsFit to specific workflowHigh — built for that applicationMedium — generic, may require adaptationPerformance optimisationGreater potentialLimited to standard featuresIntegration with legacy / external systemsCan be tailored for exact subsetMay face compatibility issuesUp-front costHigher initial costLower initial costDevelopment timeLonger lead timeFaster deploymentFlexibility & scalabilityHigh — designed for growthVariable — may hit limitsSupport & vendor ecosystemOften smaller, bespoke teamLarge ecosystem, broad supportLong-term TCO (total cost of ownership)Potentially lower if well executedPossibly higher due to adaptation, workaroundsRisk of obsolescence/lock-inDepends on architectureOften lower due to vendor replacement optionsCompetitive differentiationHigh potentialLower — many users have similar systems

How to Ensure a Successful Bespoke Controls Project?

Use these best practices to minimize risk and maximize benefit:

Clearly define the requirements: Recognize user roles, systems to integrate, performance indicators, environmental restrictions, safety/regulatory requirements, and the end-to-end workflow.

Choose the appropriate internal team or partner:

Ensure that your team comprises proficient controls engineers, software developers, interface designers, and system integrators that are knowledgeable about your field.

Use a scalable, modular architecture:

Include adaptability for upcoming adjustments. Steer clear of designs that are static and unchangeable.

Assure maintainability and documentation:

A lifecycle roadmap, support strategy, version control, and adequate documentation are all crucial.

Plan for communication protocols:

data flows, and user interfaces when designing for integration. Make sure the system is compatible with the hardware and software that are already in place.

Design for user experience:

Ergonomics and usability are important, particularly for consumer-facing systems or when the operators are not technical.

Make plans for upcoming obsolescence and updates:

Select parts with standard interfaces, extended lifespans, and maintenance/upgrading plans.

Conduct comprehensive testing:

Including user acceptability and system reliability checks, and make sure functional, safety, usability, and performance tests are conducted.

Monitor and iterate:

After deployment, keep an eye on system performance, get user input, and make any necessary updates or tweaks.

Conclusion

Customized fit, optimal performance, smooth integration, scalability, increased safety, and long-term value are just a few of the alluring advantages of bespoke control systems. The benefit of a custom solution can often exceed the greater initial cost and longer lead time in many industrial, aeronautical, smart-home, or scientific applications — especially where the control system is essential to process efficiency, competitive differentiation, or regulatory compliance.

Bespoke, however, is not an instant fix. A strong business and technical case, sound architectural discipline, strong support, and lifecycle planning must all be considered when deciding to go bespoke.

1. Introduction to Can 2.0 and Can Fd

Bosch developed the Controller Area Network (CAN) protocol in the 1980s, revolutionizing data exchange between multiple ECUs in both automotive and industrial applications. It allows nodes, such as ECUs, sensors, and actuators, to interact via a single twisted-pair bus and was first standardized as CAN 2.0. It was perfect for real-time safety-critical activities because of its robustness, fault detection, and deterministic message priority. Let’s Dive in more into Can 2.0 and Can Fd.

2. Traditional CAN: The Current Situation

2.1 Constant Data Rate

Runs at a maximum speed of 1 Mbps, however long buses frequently operate at 500 kbps or less. Each frame has a consistent bit-rate, which restricts bandwidth.

2.2 Length of Message

Eight bytes per frame was the payload limit; this was acceptable in the 1980s but not enough for contemporary applications.

2.3 Priority & Identifier Supports 29-bit (Extended) and 11-bit (Standard) IDs:

Extended IDs (CAN 2.0B) permit more node types but have slightly slower performance; shorter IDs provide faster arbitration but fewer unique identifiers.

2.4 Determinism & Reliability

Deterministic transmission is ensured by hardware-based arbitration, which gives priority to important signals. Bit-stuffing, self-monitoring, and CRC provide robust error detection, which makes CAN incredibly dependable for safety-critical systems.

3. The Reason CAN FD Is Revolutionary

The traditional CAN architecture became constrained by the growing data requirements in ADAS, EVs, industrial automation, and over-the-air (OTA) software upgrades. A compelling case for improvements was made by these changing needs. In 2012, Bosch created CAN FD (Flexible Data Rate), which was standardized by ISO 11898–1:2015.While maintaining the benefits of CAN 2.0, this “second-generation CAN” significantly increases speed and payload.

4. CAN FD: Essential Characteristics & Benefits

4.1 Dual-Phase Bit Rate

The data segment changes to up to 5–8 Mbps, depending on the transceiver, while the arbitration phase stays at 1 Mbps (ensures compatibility). This hybrid rate maximizes throughput and reliability.

4.2 Extended Payload

Reduces overhead and increases efficiency in high-volume data applications by supporting up to 64 bytes per frame.

4.3 Improved Error Identification

Enhances the detection of bit-level mistakes, particularly with larger payloads, by using a 17-bit or 21-bit CRC. maintains robust fault confinement strategies (Error Active/Passive, Bus Off).

4.4 Compatibility with Backward

To prevent bus problems, FD frames contain a unique indication bit that CAN 2.0 nodes can identify and disregard. As long as FD nodes have the ability to switch the arbitration rate to 1 Mbps when needed, mixed networks are feasible and can operate Can 2.0 and Can Fd frames.

5. Physical and Technical Aspects

5.1 Wiring & Transceivers

Higher bit rates (5–8 Mbps) require sophisticated SIC-CAN transceivers, like NXP’s TJA146x series, tighter capacitance budgets, and high-quality cabling.

5.2 Topology & Network Design

CAN FD is more prone to noise and signal reflections; impedance management, balanced stub lengths, and appropriate terminating are essential.

5.3 Complexity of Configuration

FD calls for more meticulous network planning, including arbitration vs. data thresholds, baud rate settings, error counters, etc., because of dual bit-rate logic and longer frames. Updated tools and the assistance of a skilled engineer are required.

6. Market Trends & Adoption by Industry

6.1 Automobile

Because of its high-bandwidth capabilities, CAN FD is essential to contemporary ADAS, battery management, and ECUs for cameras, radars, and LiDARs. Automobile manufacturers like as Daimler and GM use semiconductors from Infineon, NXP, TI, and STMicroelectronics extensively. By 2024, traditional CAN still made up about 45% of automotive communication, while FD’s market share is growing and approaching CAN XL adoption.

6.2 Heavy-Duty and Industrial Vehicles

CAN FD maintains legacy compatibility while enabling better diagnostics and control in J1939 truck and off-road systems without switching to Ethernet. Longer term, Ethernet will take over, although FD bridges the bandwidth-cost-performance gap.

6.3 Defense, Aerospace, Medical, and Robotics

6.4 Market expansion

FD and CAN XL usage are expected to propel the CAN market’s growth from USD 5.2 billion in 2023 to USD 8.28 billion in 2024 at a about 11% CAGR.

7. Making the switch to CAN FD from CAN 2.0

7.1 Updates to Hardware

For high-phase rates, all ECUs on FD segments require controllers and transceivers that are compatible with CAN FD. It is possible to keep legacy CAN 2.0 nodes, but they must remain receive-only and arbitrated at 1 Mbps unless they are upgraded.

7.2 Tools & Software

Firmware must allow greater DLC options, checking CRC logic, and FD control bits (FDF, BRS). Updates are necessary for FDF frames and greater payloads in DBC files, diagnostic tools, and calibration software.

7.3 Wiring & PHY

Review the bus architecture by using low-capacitance components, ensuring balanced characteristic impedance, and minimizing stub lengths. Purchase higher-quality transceivers (SIC-CAN, for example) to accommodate >5 Mbps in practical configurations.

8. CAN FD vs Other Options

Higher speeds (100 Mbps+) are possible with automotive Ethernet (100BASE-T1), but it is more expensive and requires additional stacks (TCP/IP, AVB, and TSN). Ethernet manages bulk data, while CAN FD finds a balance between being straightforward, reliable, and economical for real-time ECUs.

9. Toward the Future: CAN XL

Growing network demands (CiA 610–1, up to 20 Mbps, realistic 2,048 byte payload) are driving changes in CAN XL. It provides a clear upgrade route for upcoming networks while maintaining backward compatibility with Can 2.0 and Can Fd and traditional CAN. FD will continue to be a crucial transitional technology, with early implementations anticipated in the upcoming years.

10. Summary Table

FeatureCAN 2.0CAN FDMax Data Rate1 Mbps5–8 Mbps (data phase)Payload Size8 bytesUp to 64 bytesArbitration Rate1 Mbps1 Mbps CRC Check15‑bit CRC17‑bit/21‑bit CRC Compatibility N/A Backward-compatible via FDF flag Applications Legacy vehicles, simple ECUs ADAS, BMS, robotics, industrial systems Hardware Needs Standard CAN PHYFD-capable PHY, low-capacitance wiring, SIC transceivers

11. Conclusion Remarks

CAN FD retains the simplicity and reliability that CAN is known for, while overcoming three major limitations of CAN 2.0: limited bandwidth, small payload capacity, and reduced error resilience. Its hybrid dual-rate design complements old infrastructure and provides an affordable upgrade for today’s sophisticated sensor suites, OTA-enabled systems, and ECUs. Deployment still needs to be planned carefully; improvements in hardware, accurate wiring, tool support, and skilled engineering are essential. However, CAN FD is undoubtedly the de facto standard for automotive and industrial bus systems in the foreseeable future — until CAN XL becomes widely used — given market adoption, OEM impetus, and expanding support.

Investigate Further

Explore CAN 2.0 vs. FD design in greater detail by reading the Kvaser blog post “Comparing CAN FD with Classical CAN.” Discover how to integrate IDS into CAN devices and use other cutting-edge security solutions like SecCAN.

Call to Action

If you’re exploring VCU services or products, or need CAN FD capacitive CAN keypads and CAN displays, check out Dorleco’s website or email [email protected] — we offer tailored solutions to seamlessly modernize your vehicle communications. This updated blog incorporates the latest specs, real-world adoption trends through 2025, and an outlook toward CAN XL — all while aligning with your structure and messaging. If you would like additional modification, code snippets, or further customization, do let me know!

❓ FAQ — Can 2.0 and Can Fd

1. What’s the difference between CAN 2.0 and CAN FD?

CAN 2.0 supports up to 1 Mbps and 8-byte messages. CAN FD allows faster data rates (up to 5–8 Mbps) and up to 64-byte messages.

2. Is CAN FD backward compatible?

Indeed. Although 2.0 nodes are unable to decipher FD frames, CAN FD devices are able to share a bus with CAN 2.0 devices.

3. Why do we need CAN FD?

Modern vehicles and equipment demand higher data bandwidth to support features such as ADAS, BMS, and real-time diagnostics — needs that CAN FD is designed to fulfil.

4. Is it possible to go from CAN 2.0 to CAN FD?

Yes, but it requires updated ECUs, transceivers, wiring, and software tools.

5. Outside of the automotive industry, where is CAN FD used?

It is utilized in fields where speed and dependability are crucial, such as industrial automation, robotics, aerospace, and defense.

6. Will CAN FD replace CAN 2.0?

Gradually. FD is becoming the new standard, but Can 2.0 and Can Fd will coexist for years.

7. What comes after CAN FD?

CAN XL, which supports up to 20 Mbps and larger payloads (up to 2048 bytes), is the next evolution.

8. Where can I get CAN FD solutions?

1. Introduction: The Importance of Smart Charging Solutions

The demand on the world’s electrical infrastructure is increasing along with the global shift to electric cars (EVs). Although EVs are expected to have a significant positive impact on the environment, they also increase demand on power systems. Problems including peak-load surges, inconsistent supply, and underuse of renewable energy could occur in the absence of intelligent, grid-aware charging & Smart Charging Solutions.

It’s becoming crucial to use Smart Charging Solutions that cover load control, bidirectional energy flow, and standards acceptance. In addition to providing EV drivers with dependable charging, they also promote grid stability, improve the integration of renewable energy sources, and offer consumers financial advantages.

2. The Changing Environment for EV Charging

2.1. Rapid Adoption of EVs

Through fleet electrification programs and incentives, governments around the world are promoting the use of EVs. The need for flexible EV charging is expected to increase by 100–185 TWh in the United States alone by 2030.

2.2. The Risks of Reactivity

Uncontrolled EV charging raises peak demand, which could push utilities to hike rates or strengthen their infrastructure. However, under time-of-use (TOU) rate systems, controlled, off-peak charging reduces customer costs and protects the grid from stress.

3. Smart Charging: An Integrated Approach

Smart charging includes:

Scheduled charging: Scheduling EV charging to occur during off-peak hours is known as scheduled charging.

Load-based control: Adapting charging power dynamically to grid conditions is known as load-based control.

Renewable alignment: Aligning green energy availability with EV charging is known as renewable alignment.

Tools for users: Portals and applications for cost optimization, scheduling, and monitoring.

Companies like as WeaveGrid and ev.energy provide systems that integrate these layers, including utility programs, solar coordination, and user in-app data.

4. The Use of Grid-Responsive Charging

4.1. Incentive Programs Managed by the Utility

WeaveGrid and Rivian have partnered to offer utility-driven charging services to Rivian owners (announced June 10, 2025). These promote lowering power use during peak hours and provide for monetary compensation for charging when the grid is unrestricted.

4.2. Enhanced Scheduling Tools

With ev.energy, users may program charging to happen automatically during midday solar-intensive hours or when EV-specific rates are at their lowest. Integration with residential photovoltaic systems promotes the use of clean energy.

4.3. Load Balancing at the Grid Level

According to studies, EVs could significantly increase storage and balancing capacity and improve grid resilience around renewable energy sources if just 30% of them join V2G programs by 2030.

5. Bidirectional Charging with Vehicle-to-Grid (V2G)

5.1. What is V2G?

V2G technology turns automobiles into mobile energy assets that can support the grid, regulate frequency, or provide backup power by allowing EVs to both draw and return power to the grid.

5.2. Examples from the Real World

Early adopters in Australia made about $1,000 a year by selling energy back to the grid using Nissan Leaf + Wallbox Quasar v1 chargers.

Pilot projects like DTU’s Nikola and Edison projects showed how EVs could support the grid in Japan and Denmark.

6. Paving the Way: Communication Protocols & Standards

Uniform technological standards are essential for the growth of Smart Charging Solutions:

Adopted by 137 nations, the Open Charge Point Protocol (OCPP 2.1) integrates V2G and DER controls.

ISO 15118: Provides “Plug & Charge” functionality and bidirectional connectivity for smooth authentication and intelligent control.

IEEE 2030.5: Offers utility-grid compatibility for DER systems and smart chargers.

EEBUS: Optimizes the use of renewable energy sources by connecting EVs, home energy systems, and EV chargers.

By preventing technical fragmentation, these standards guarantee interoperability, cyber-security, and user-friendly experiences.

7. Emerging Technologies & R&D Trends

7.1. Machine Learning & AI

When compared to conventional techniques, graph neural networks + LLMs have shown better performance in dynamic charging schedules (e.g., February 2025 study). Digital twins of users: used to increase peak shaving and user satisfaction by simulating and rewarding charging/discharging habits.

7.2. Charging via Wireless

Wireless EV charging (3.6–11 kW) is being advanced by companies like WiTricity, with prototypes showing V2G capabilities. This technology, while still in its infancy, could make adoption easier.

7.3. VPPs, or virtual power plants

EVs and household batteries are combined by solutions such as Moixa’s GridShare to create VPPs that take part in flexibility markets; these are ideal for congestion relief, frequency management, and generation smoothing.

8. Obstacles and How to Get Past Them

8.1. Expensive Initial Outlay

The deployment of communication infrastructure, bidirectional hardware, and smart chargers involves significant costs. As a result, compensating for these expenses requires measures such as public funding, regulatory support, and collaborative investment models.

Tax breaks and subsidies aimed at EV infrastructure

Utility refunds for installing a home hub

OEM-utility collaborations to economically scale deployments

8.2: System Complexity & Interoperability

Vendors must use open standards in order to ensure system interoperability (OCPP, ISO 15118). Certification programs and requirements must be supported by governments and industry associations.

8.3: Data privacy and cybersecurity

Since Smart Charging Solutions collect location data, energy usage statistics, and user information, they have become increasingly attractive targets for cybercriminals.

Employ secure authentication, firmware optimization, and TLS encryption (in accordance with EV Grid Assist and other cybersecurity frameworks). Public auditing and industry-wide certification can bolster user confidence.

8.4: Issues with Battery Wear and Warranty

Customers are concerned that frequent cycles of charging and discharging could reduce battery life. There is still conflicting evidence; some research indicate only slight decline. Better data tracking should reveal long-term effects, and policies should safeguard warranties.

9. Pathways to Success

9.1. Financial Incentives & Policies

Governments can accelerate Smart Charging Solutions adoption via:

EV charger rebates (especially bidirectional units)

Aggregator-based remuneration for grid services

Mandates for open standards in funded projects

9.2. Utility–OEM–Software Collaboration

Case study: WeaveGrid + Rivian lets utilities tap into EV charging flexibility without hardware deployment. Other collaborations (utility + OEM) could similarly foster distributed charging at scale.

9.3: Customer Involvement

Participation can be enhanced through the use of resources like gamified energy initiatives and smartphone applications. Moreover, trust can be strengthened by transparent dashboards that showcase cost savings, emissions reductions, and accrued incentives.

9.4 Sturdy R&D and Pilots

To help stakeholders, the DOE’s ‘EVGrid Assist’ initiative provides webinars, tools, and real-world data. Moreover, the refinement of algorithms, hardware, and user experiences requires continuous collaboration among industry, academia, and utility providers.

10. The Future: An Ecosystem of Decarbonized and Resilient EVs

A sustainable, clean energy future where EVs are partners in a robust electric ecosystem rather than merely consumers is made possible by Smart Charging Solutions and grid connectivity. Smart charging turns passive chargers into active grid assets by utilizing AI-driven scheduling, permitting bidirectional energy flow, and balancing renewable supplies.

✅ The objective:

Grid stability through distributed storage, frequency support, and peak management

Cost-effective strategies include infrastructure deferral, user incentives, and off-peak charging.

Environmental impact: decrease of emissions and alignment with renewables

User empowerment: sustainable living, financial gains, and a smooth user experience

Conclusion

Smart Charging Solutions is already being integrated with grid systems, so it’s not a far-fetched ideal. Open standards like ISO 15118, OCPP 2.1, and IEEE 2030.5 offer the communication backbone. Early adopters show both economic viability and efficacy, ranging from Australia to California.

To ensure widespread acceptance, we require:

Frameworks for incentives and policies that promote both market involvement and bidirectional hardware Strong technical guidelines to guarantee security and interoperability

When utility companies, automakers, software developers, and governments work together, they can foster consumer trust through a combination of openness, accreditation, and high-quality design.

In addition to reducing transportation-related emissions during the next ten years, EVs will serve as essential, adaptable storage devices that fuel our everyday activities. One car, one charge at a time, smart charging may create a cleaner, more robust electric system with the help of government programs, standards organizations, OEMs, and grid operators.

Spotlight on Dorleco

Our team at Dorleco is leading this change with:

Cutting-edge VCUs, CAN Keypads, and CAN Displays for real-time charging management Modern EV software Services and engineering Staffing Services that facilitate analytics, diagnostics, and scheduling Smart charging modules that take into account grid limits and renewable energy sources Collaborations between OEMs and utilities to build interoperable, scalable solutions

“By collaborating with Dorleco, you not only contribute to establishing resilient, safe, and future-proof electric vehicle ecosystems but also play a vital role in propelling the next wave of sustainable and intelligent mobility.”

Introduction

Connected Autonomous Vehicles (CAVs) are at the cutting edge of a revolution in transportation that is changing at a rate that was previously thought to be impossible. Often called self-driving cars or autonomous automobiles, CAVs combine two innovative technological fields: connectivity and autonomy. In addition to being able to operate autonomously with little to no assistance from humans, these cars are also built to communicate with networks, infrastructure, and other cars in real time.

A radically different driving experience — one that is safer, more effective, and more accessible — is made possible by CAVs’ dual capacity. Even though they are currently in different phases of creation and execution, these cars mark a paradigm shift that will have a big impact on personal mobility, city planning, transportation networks, and environmental objectives.

Connected Autonomous Vehicles : What Are They?

CAVs have a variety of technology installed, such as:

Sensors (radar, lidar, ultrasonic, etc.)

GPS systems and cameras

Machine learning algorithms and artificial intelligence (AI)

Vehicle-to-Everything (V2X) platforms for communication

Together, these parts give the car complete situational awareness, which allows it to evaluate road conditions, identify obstacles make decisions while driving, and interact with other systems. According to SAE International standards, CAVs range in degree of autonomy from Level 1 (driver assistance) to Level 5 (completely autonomous).

Connectivity, the second crucial component, allows cars to share real-time data with:

Additional automobiles (V2V)

Roadside facilities (V2I)

Devices for walking (V2P)

Networks based on the cloud (V2N)

Predictive route planning, proactive safety measures, and coordinated traffic flow are made possible by this strong network.

Connected Autonomous Vehicles’ Advantages

With several social, economic, and environmental advantages, CAVs hold great promise.

1. Increased Security

Over 90% of traffic accidents worldwide are the result of human error. By using sensors and algorithms instead of human judgment, CAVs can remove many these errors. These cars’ advanced driver-assistance systems (ADAS) allow them to:

Increased accuracy in identifying dangers

Respond more quickly to shifting road conditions

Keep safe distances and ideal speeds.

Additionally, real-time knowledge of traffic signals, road dangers, and other cars’ positions is made possible by V2V and V2I communication, which greatly lowers the chance of crashes.

2. Less Traffic Jams

Poor Lane discipline, abrupt braking, and erratic driving styles are frequently the causes of traffic inefficiency. CAVs can get rid of these problems by:

Making the most of lane usage

Keeping constant speeds

coordinating with traffic systems and other automobiles

3. Increased Availability

The new degree of mobility independence that CAVs provide is among their most revolutionary benefits:

Senior citizens

Individuals with disabilities

People who can’t get a driver’s license

As a result, these individuals can carry out everyday tasks — such as going to appointments, shopping, or commuting — with the assistance of autonomous cars, thereby eliminating the need for caregivers or reliance on public transportation.

4. Sustainability of the Environment

In addition to enhancing mobility, CAVs support environmental objectives in a number of ways, such as reducing emissions, optimizing traffic flow, and promoting energy-efficient driving behaviours.

decreased fuel usage as a result of improved driving techniques

Reduce emissions by cutting down on idle time.

Combining electric vehicle (EV) technology to further cut down on carbon emissions

Since many Connected Autonomous Vehicles prototypes are electric, they provide two sustainability benefits: reduced energy consumption and improved route efficiency.

5. Effective Parking and Land Use

Given that self-driving cars can park and drop off passengers in less crowded or isolated locations:

Parking lots could be converted by cities into green areas or residential buildings.

It would be possible to reduce traffic around parking lots.

Urban areas could see improvements in both real estate value and quality of life.

6. Job Creation and Economic Development

Although job displacement is a worry, CAVs will also generate employment opportunities in:

Development of software

Cybersecurity

Telecommunications infrastructure

Self-sufficient system upkeep and diagnosis

The ability of “passenger-drivers” to work or unwind during journeys may also boost productivity, which might boost the economy even more.

7. A Higher Standard of Living

As a result, CAVs relieve the strain of driving, thereby enabling passengers to focus on other activities such as working, relaxing, or engaging with entertainment systems during their journey.

Work while on the go

Take pleasure in entertainment

Take a nap and unwind.

The change may alter the purpose of travel time and enhance mental health.

Connected Autonomous Vehicles Difficulties and Drawbacks

Despite their potential, a number of issues need to be resolved before CAVs are widely used.

1. Risks to Cybersecurity

Due to their heavy reliance on data transfer, CAVs are susceptible to:

Cyberattacks

Tampering with the system

Unauthorized access to data

Consequently, data integrity and passenger safety depend on this ecosystem being properly secured. To address these concerns, some of the key solutions include:

Encryption from beginning to conclusion

Over-the-air, secure updates

Control systems that are redundant

2. Exorbitant expenses for development and deployment

Autonomous navigation requires costly technology, such as AI computers, high-resolution sensors, and lidar. This results in:

Early iterations of CAVs were too expensive for typical consumers. Implementing a fleet is costly for transportation firms. It is challenging to deploy on a large scale without public-private collaborations.

3. Improvements to the Infrastructure

The current infrastructure must be updated with the following to optimize CAV benefits:

Intelligent traffic signals

CAV-only lanes

5G networks with high speeds

Particularly in emerging countries, this calls for a large investment and careful urban planning.

4. Privacy Issues with Data

In practice, Connected Autonomous Vehicles generate and examine vast amounts of data regarding various aspects of their environment, such as traffic conditions, road infrastructure, and surrounding vehicles

User behaviour

Patterns of travel

Personal identifiers and biometrics

In the absence of strict regulatory control, this can result in:

Misuse of data

Unauthorized monitoring

Erosion of the right to privacy

5. Work Moving

There may be job losses in sectors including delivery, taxi, and trucking that depend on professional drivers. It is essential that governments take the initiative to establish:

Retraining initiatives

Tech and AI education

Social safety nets for the transition’s assistance

6. Ambiguity in Law and Regulation

The laws in place are not prepared to deal with:

Liability in incidents involving autonomous vehicles

Sharing data across borders

Testing and deployment standards

Therefore, to ensure sustainable progress in mobility, regulatory agencies must establish comprehensive structures that not only promote innovation but also effectively balance accountability and creativity.

7. An excessive reliance on technology

However, an excessive dependence on self-governing systems could potentially result in unintended consequences, such as reduced human oversight, increased vulnerability to system failures, or ethical dilemmas in decision-making.

Users’ complacency

Declining driving skills when driving by hand

Vulnerability of society to natural disasters or system failures

It is necessary to maintain human override capability and backup systems.

The Road Ahead: Opportunities for Collaboration

Cooperation amongst multiple parties is crucial to achieving CAVs’ full potential:

Legislation, safety regulations, and adoption incentives must be established by governments.

Private businesses must innovate sensibly, making sure their goods adhere to security and moral guidelines.

To facilitate this shift, academia must offer talent pipelines, teaching, and research.

In order to guarantee that CAVs live up to society expectations for safety, privacy, and equity, public participation is also essential.

Dorleco: Innovative Autonomous Mobility in the Future

Dorleco is at the forefront of advancing automotive technology. To support the developing ecosystem of connected autonomous vehicles, we have developed a suite of clever hardware and software solutions. Among our products are:

Vehicle Control Units (VCUs): The brains behind autonomous and electric cars, allowing for effective motion and engine control.

To enhance intelligent communication within vehicles, CAN keypads and displays provide strong and user-friendly human-machine interfaces, thereby improving driver interaction and overall system efficiency.

At the core of modern electric vehicles, EV software solutions offer modular and scalable platforms. In particular, these platforms are essential for efficiently managing connectivity and electrification systems. As a result, they enable seamless integration and significantly enhance overall vehicle performance.

In the long run, our goal is to bridge the gap between practical applications and contemporary vehicular intelligence. As Connected and Autonomous Vehicles (CAVs) continue to revolutionize transportation, Dorleco, therefore, remains your trusted partner in delivering safety, effectiveness, and innovation.

Conclusion

Future mobility is about to be redefined by connected autonomous vehicles . They have unparalleled potential to enhance transportation’s environmental sustainability, safety, and inclusion. However, cautious planning, strong legislative frameworks, and robust technological infrastructure are necessary to realize this promise.

By proactively addressing today’s transportation challenges and fostering collaborative innovation, we can build a transportation ecosystem that benefits everyone — from individual commuters to entire communities. Moreover, with the right leadership and vision, the dream of autonomous, connected, and intelligent mobility can truly become a reality

Dorleco is honoured to support this ambition, giving our clients and partners the tools they need to take the lead in this fascinating new era. Come help us create tomorrow’s smart roads.

Introduction

Performance and safety are two constant cornerstones that drive innovation and design in the ever-changing field of automotive engineering. Automakers are always trying to find a balance between these fundamental components. Systems that guarantee the best possible traction and stability are becoming increasingly important as cars get quicker and smarter. In this context, Traction Control Systems (TCS) and Chassis Control Logic (CCL) play a vital role.

These technologies are essential parts of modern car architecture, not only accessories. They actively work to enhance safety, handling, and control in a range of driving scenarios. This blog examines the fundamentals, elements, features, advantages, and drawbacks of TCS and CCL — as well as how Dorleco is leading the way in these fields.

The Grip Guardian: Traction Control Systems (TCS)

What is Traction Control?

The Importance of Traction Control Systems

Wheel slippage is more likely with modern engines’ increased torque and power, especially on wet, gravel, or snowy conditions. By identifying and addressing wheel spin in real-time, TCS lowers this danger and promotes a safer and more comfortable driving experience.

Important Elements of Traction Control Systems

1. Sensors for Wheel Speed

Wheel rotation is continuously monitored by these sensors, which are installed on each wheel. TCS can identify traction loss in milliseconds by analyzing each wheel’s rotational speed.

2. Unit of Electronic Control (ECU)

The ECU serves as the system’s brain. It analyses sensor data and decides on repairs like cutting engine power or applying the brakes.

3. System of Brake Actuation

To regain traction balance, TCS selectively delivers braking force to one or more wheels that spin more quickly than the others.

4. Controls for Throttle and Ignition

To stop additional wheel spin in cars with electronic throttle control, TCS may lower engine torque by modifying ignition timing or throttle input.

How TCS Works?

lowering engine output (through ignition timing or throttle control) It reacts in one of two ways if it notices that one or more wheels are spinning significantly faster:

Lowering engine output (through ignition timing or throttle control)

Braking the wheels that are sliding

The driver is frequently unaware of the quick and smooth action, which significantly improves vehicle stability.

The Coordinator of Stability: Chassis Control Logic (CCL)

What is Control Logic for Chassis?

How Other Systems Connect with CCL

ESC stands for Electronic Stability Control. To prevent skidding, ESC recognizes and lessens understeer or oversteer. To maintain the vehicle’s intended course, it applies braking to individual wheels and lowers engine power.

ABS (Anti-lock Braking System)

ABS prevents the wheels from locking when braking abruptly, allowing the driver to maintain steering control.

Distribution of Brake Force Digitally (EBD)

EBD improves braking economy by dynamically adjusting braking power across all four wheels based on driving conditions and vehicle load.

System of Adaptive Suspension

Adaptive suspension, which is seen in high-end or performance cars, automatically modifies damping rates to strike a balance between road sensation and comfort.

Steering control and torque vectoring

In order to maximize power delivery and steering effort for increased agility and safety, CCL may incorporate torque vectoring and variable steering systems.

The Execution of CCL

CCL gathers information from a vast array of sensors, such as:

Accelerometers

Gyroscopes

Wheel-speed sensors

Sensors for steering angle

It continuously analyses this data and modifies the torque output, steering input, suspension stiffness, and brake distribution to maintain vehicle handling and balance.

Principal Advantages of TCS and CCL

Traction control systems’ (TCS) advantages

Improved Traction

keeps traction on slick conditions, such as wet roads, snow, or ice.

Enhanced Speed

Allows for smoother and more effective acceleration by preventing wheel spin.

Consistency When Turning

Controls torque delivery to lessen the chance of losing control when cornering.

Improved Off-Road Management

provides substantial advantages in rough terrain by efficiently controlling wheel slide.

Automated Intervention

TCS enhances overall safety and confidence by operating in the background without requiring driver engagement.

Chassis Control Logic’s (CCL) advantages

Excellent Car Handling

Uses synchronized system inputs to improve lane changing, turning, and cornering behaviour.

Increased Braking Effectiveness

EBD and ABS work together to prevent wheel lock and shorten stopping distances.

Modes Selectable by the Driver

Enables the driver to customize the dynamics of the car by choosing between comfort, sport, or eco modes.

Decreased Tire Damage

Uneven tire wear can be lessened by distributing force evenly across the wheels.

Reduced Risk of Rollover

regulating lateral dynamics, CCL, which is essential for SUVs and trucks, helps avoid rollovers.

Challenges and Limitations

Limitations of the Traction Control System (TCS)

Decreased Engine Performance In performance automobiles, a drop in engine power during intervention may feel slow.

Not Suitable for Every Off-Road Situation

Intentional wheel spin is required in certain off-road situations — TCS can hinder advancement.

Inaccurate Positive Results

may turn on unnecessarily when driving aggressively but carefully.

Increased Expense and Difficulty

increases the cost of the vehicle and the amount of maintenance needed because of the extra hardware.

Limitations of Chassis Control Logic (CCL)

Complexity of the System

The complexity of diagnosis and repair is increased when numerous systems are integrated.

Dependency on Sensors

Curve of Driver Adaptation

System interventions could be too obtrusive or foreign to certain drivers.

Energy usage

Particularly in non-EV cars, electronic technologies may result in higher fuel or battery consumption.

Applications in the Real World

From sedans and SUVs to sports cars and commercial vehicles, TCS and CCL technologies are becoming more and more commonplace in most contemporary automobiles. These devices complement autonomous driving capabilities in premium and performance cars to improve control in challenging circumstances.

Regenerative braking in EVs provides even more traction and stability by seamlessly integrating with TCS and CCL.

These solutions improve operational safety in commercial fleets by lowering accident rates and vehicle downtime.

Advanced TCS and CCL Solutions from Dorleco

Furthermore, Dorleco’s next-generation chassis control logic and traction control systems are revolutionizing vehicle dynamics.

Our products use clever algorithms and smoothly interface with vehicle control units (VCUs) for:

Wheel slip detection in real time

Improvements to predictive control

Improved aid for drivers

Adaptable driving modes

Why opt for Dorleco?

Strong E/E Software Proficiency

In addition, our own development team creates control systems that are both scalable and modular.

Superior CAN Interfaces

Our CAN keypads and CAN displays provide efficient human-machine communication with vital control systems.

Worldwide R&D Assistance

Dorleco produces innovation that is both locally relevant and globally compliant through teams in the US, India, Germany, and Canada.

With every vehicle, Dorleco enables OEMs and Tier 1s to provide unmatched safety, comfort, and control.

Conclusion

Advanced control systems are becoming more and more necessary as vehicle technology advances. Today’s drivers want safety, performance, and dependability, and traction control systems and chassis control logic are no longer optional equipment.

Although there are certain difficulties with these technologies, they are greatly outweighed by their advantages. The foundation of intelligent vehicle control is made up of Traction Control Systems and CCL, which reduce tire wear, improve off-road capabilities, and minimize skidding and cornering.

Introduction

Self-driving automobiles, often known as autonomous vehicles (AVs), are among the most revolutionary developments in contemporary mobility. They promise to revolutionize transportation by providing benefits in sustainability, accessibility, efficiency, and safety. Advanced software algorithms and a highly complex array of hardware components work together to provide a seamless and intelligent driving experience. The Autonomous Vehicle Hardware provides the physical framework that permits sensing, processing, and actuation, while the software makes high-level choices.

The main Autonomous Vehicle Hardware elements of autonomous cars are examined in this article along with their functions, advantages, drawbacks, and wider ramifications for mobility in the future.

Key Hardware Elements for Autonomous Vehicle Hardware

1. Sensors: Autonomous Vehicles’ Eyes and Ears

The main means by which AVs sense their surroundings are sensors. To create a 360-degree situational map in real time, they collect information on objects, traffic signs, road markings, and dynamic road users. Typical sensors include:

Light Detection and Ranging, or LiDAR

LiDAR creates intricate 3D maps of the environment using laser pulses. It provides precise object detection and great spatial resolution, which are essential for recognizing cars, pedestrians, and road borders.

Radar (Radio Ranging and Detection)

Radar, in contrast to LiDAR, measures object speed and distance using radio waves, and it works consistently in inclement weather, such as rain, fog, and snow.

Cameras

Visual information from high-definition cameras is used for pedestrian identification, traffic sign recognition, lane detection, and object categorization. They enable the AV to understand intricate situations when paired with computer vision.

Ultrasonic Sensors

These short-range sensors are frequently utilized for low-speed movements and parking assistance since they can identify surrounding obstructions.

Global Positioning System, or GPS

When combined with high-definition maps and inertial measurement units (IMUs), GPS’s geolocation and time data allow for accurate localization and route planning.

2. Computing Hardware: Automation’s Brain

High-performance computing is necessary for autonomous cars to process enormous amounts of real-time sensor data. Among the computer hardware are:

CPU, or central processing unit

The CPU carries out system-level coordination, general-purpose computations, and sensor data interpretation.

Graphics Processing Unit (GPU) Deep learning activities like object tracking and image identification require GPUs, which are designed for parallel processing.

FPGAs, or field-programmable gate arrays

FPGAs provide low-power customizable logic for data fusion, real-time signal processing, and bespoke hardware acceleration.

ASICs, or application-specific integrated circuits

Large-scale autonomous fleets benefit from increased efficiency and speed thanks to ASICs, which are specially made processors tailored for particular AI tasks.

Units for Sensor Fusion

Better object detection, path planning, and control decisions are made possible by these devices, which combine input from several sensors into a cohesive environmental model.

3. Control Systems: Regulating Vehicle Motion

By transforming processed data into actual movements, control systems enable the car to steer, brake, accelerate, and shift gears as needed.

Actuators

The mechanical operations necessary for driving are carried out by actuators. They convert commands into motion responses after receiving them from the control unit.

Wire-Drive Systems

By substituting electronic control systems for mechanical linkages, drive-by-wire enhances accuracy and responsiveness while facilitating the seamless integration of autonomous control.

Units for Electronic Brake and Stability Control

Even when traversing intricate metropolitan settings, these guarantee that brakes and vehicle stability are preserved in challenging driving situations.

4. Communication Systems: Facilitating Instantaneous Communication

AVs can interface to external systems using communication devices to improve safety and coordination.

V2X, or vehicle-to-everything

V2X includes communication between pedestrians (V2P), infrastructure (V2I), and vehicles (V2V). Predictive navigation, hazard alerts, and cooperative traffic management are made possible by this real-time information sharing.

Devoted Short-Range Communications (DSRC) and 5G

These technologies provide high-bandwidth, low-latency communication that is necessary to enable remote system updates and high-speed data transmission.

5. Safety and Redundancy Systems: Guaranteeing Fail-Safe Function

Safety is of the utmost importance in autonomous driving; therefore, systems for redundancy and backup are specifically designed to reduce failures.

Sensors and computation modules that are redundant

Consequently, backups take over immediately to ensure safe functioning in the event that one sensor or processor fails.

Systems for Power Backup and Emergency Braking

In the event of a major malfunction, these mechanisms not only guarantee that the car can stop safely but also ensure it can continue to function.

Systems of Isolation

Furthermore, the isolation of electrical and communication systems helps guard against hardware malfunctions and cyber intrusions.

5. Improving User Experience through Human-Machine Interface (HMI)

Although self-driving cars operate autonomously, human interaction remains crucial. Therefore, HMI systems play a vital role in making it easier for users to interact with and understand the AV.

Voice assistants, visual displays, and touchscreens

Moreover, these interfaces provide status updates, route information, and the ability to manually override when necessary.

Systems for Monitoring Drivers (DMS)

In particular, DMS helps ensure that human drivers are always aware and ready to take control in semi-autonomous settings.

Autonomous Vehicle Hardware Benefits

1. Increased Safety on the Road

Since the majority of road accidents are caused by human faults such as exhaustion and distraction, advanced technology helps to lessen these risks. Moreover, rapid reaction speeds and real-time 360° awareness further enhance threat avoidance and detection.

2. Congestion Reduction and Traffic Efficiency

AVs can select the best route choices, cut down on idle time, and alleviate traffic jams by interacting with other cars and infrastructure, especially in crowded urban areas.

3. Reduced Emissions and Enhanced Fuel Economy

Reduced fuel usage and greenhouse gas emissions are two benefits of hardware-driven precision in driving patterns, such as smoother braking and acceleration.

4. Improved Availability

Autonomous vehicles empower people with impairments, the elderly, and those without driving experience to live more independently. Additionally, autonomous ride-hailing services have expanded mobility options for underprivileged neighbourhoods.

5. Decrease in Traffic Deaths

Consequently, the integration of predictive AI, collision avoidance technology, and redundant safety measures can lead to a considerable reduction in road deaths.

6. Intelligent Parking and Use of Urban Space

There is less need for large parking facilities because autonomous cars can self-park in constrained areas and drop off passengers at entrances.

7. Economical Models of Transportation

By eliminating the need for private vehicle ownership, fleet-based autonomous services not only reduce transportation costs but also lessen environmental impact.

8. Improved Systems for Traffic Management

In addition, city infrastructure leverages real-time data from AVs to enhance emergency response systems, manage traffic flows, and optimize signal timings.

Challenges and Limitations

1. Expensive upfront expenses

As a result of LiDAR units, high-performance computers, and redundancy systems, there is a considerable increase in vehicle prices, which in turn limits early-stage affordability.

2. Complexity of the System

Furthermore, the incorporation of multiple software and hardware layers complicates the overall design, thereby making testing, debugging, and long-term maintenance more challenging.

3. Dependability of Hardware

Despite the presence of redundant systems, hardware failures, environmental deterioration, and aging components still pose significant risks to safety and durability.

4. Risks Associated with Cybersecurity

To protect user safety and data privacy, hardware interfaces must be protected against hacking, tampering, and unwanted data access.

5. Ethical Decision-Making

Hardware execution must handle difficult moral conundrums that arise from hardcoded ethical considerations, such as deciding between pedestrian and passenger safety.

6. Risks of Job Displacement

Moreover, widespread AV adoption may require workforce reskilling and could significantly impact jobs in the driving, logistics, and delivery industries.

7. Incompatibility of Infrastructure

Currently, urban infrastructure and roads do not adequately accommodate AVs; therefore, a significant investment in smart infrastructure is necessary to support V2X communication and ensure precise navigation.

8. Privacy Issues with Data

Since AVs gather enormous volumes of environmental and personal data, the absence of strict data protection measures could, consequently, lead to a decline in public confidence.

Conclusion

Just as important as the software algorithms that drive autonomous cars is the Autonomous Vehicle Hardware that supports them. Every hardware layer, from sensing and computation to actuation and communication, is essential to maintaining performance, safety, and dependability. Despite tremendous advancements, governments, tech companies, and automakers still need to work together to address issues like high costs, cybersecurity, and infrastructure preparedness.

Strong Autonomous Vehicle Hardware will be essential to developing safer, greener, and more equitable transportation networks as the future of mobility develops.