Automotive Engineering Electric Vehicles

During a recent trip using an electric vehicle (EV), I observed an important aspect of the charging landscape: various apps showcased different charging points. Notably, Google Maps emerged as the only app displaying a comprehensive list of charging stations. However, even this platform wasn't without flaws, as some charging points marked as operational were, in fact, out of service. This inconsistency is crucial to address as we aim to enhance EV adoption, which surged by over 200% in India from 2021 to 2022, with over 1.5 million electric vehicles on the road as of 2023. Despite this rapid growth, the fragmentation among charging networks poses a significant challenge. Current data indicates that only about 30% of charging stations are listed across multiple apps, hindering drivers' ability to locate charging points easily. This variability can create confusion for users who need reliable access to charging infrastructure. To facilitate a seamless charging experience, we need standardized APIs for data sharing among networks, a unified platform aggregating charging locations, and improved real-time data on station availability. Addressing these challenges will not only simplify navigation for EV owners but also strengthen confidence in the charging ecosystem. As we scale up EV infrastructure, embracing these solutions becomes essential to ensure a robust system that supports the transition to sustainable transportation.

AI’s EV Moment: The Same 3 Mistakes Tech Providers Keep Repeating We’ve seen this movie before. EV adoption didn’t slow down because EVs “don’t work.” It slowed because the market overpromised outcomes while underestimating the ecosystem: charging availability, real-world range variability, and total cost of ownership surprises. AI is heading into the same wall. First, infrastructure. Enterprises aren’t “buying AI,” they’re buying compute capacity, data pipelines, security controls, governance, and energy-intensive operations. When power, GPUs, or data readiness become constraints, adoption turns into a waiting game. Second, capabilities vs. reality. EVs had rated range; drivers got winter range. AI has demos; enterprises get messy workflows, edge cases, and ROI that’s harder—and slower—to capture than the pitch decks implied. Third, total cost of ownership. The bill isn’t just licenses. It’s integration, observability, red-teaming, compliance, change management, and ongoing operational overhead—plus the metered nature of usage at scale. The takeaway: AI is an ecosystem adoption problem, not a feature rollout. What’s been your biggest “AI winter range” surprise so far: infrastructure, ROI, or TCO? #AI #GenerativeAI #EnterpriseAI #CIO #CTO #DigitalTransformation #CloudComputing #DataCenters #AIGovernance #FinOps #TechStrategy #EV #Innovation #OperationalExcellence

Ford’s new Universal EV Platform and Assembly Tree production system mark a bold leap into the future of electric vehicle manufacturing—one they believe could be their Model T moment for the EV era. ⚙️ Technical Highlights of Ford’s Universal EV Platform Inspired by Tesla’s “Unboxing” Method: Tesla pioneered a 3-box manufacturing approach using giga castings for the front and rear, and a structural battery pack in the center. Ford adopts a similar strategy, splitting the vehicle into three sub-assemblies: Front: - Built with large aluminum unicasting. Middle: - A cobalt- and nickel-free LFP prismatic battery that doubles as the vehicle’s floor. Rear: - Also, giga casted, reducing complexity and weight. Assembly Tree vs. Traditional Line: Instead of a single conveyor belt, Ford’s Assembly Tree uses three parallel lanes for each sub-assembly. These modules are painted and outfitted independently, then merged in the final section—streamlining the process and improving ergonomics for workers. Efficiency Gains: 20% fewer parts, 25% fewer fasteners, 40% fewer workstations, and15% faster overall assembly time. Wiring harness is 4,000 feet shorter and 10 kg lighter than previous EVs. Battery Innovation: Ford is using fast-charging LFP batteries, manufactured domestically at BlueOval Battery Park Michigan. These batteries offer durability, cost savings, and a lower center of gravity for better handling and cabin space. 🚗 Why It Matters Ford’s first product on this platform will be a midsize electric pickup, targeting a $30,000 price point and launching in 2027. The platform is designed to be scalable, affordable, and fun to drive, with OTA updates and zonal electric architecture. Toyota has already acknowledged Tesla’s influence and plans to adopt similar methods in its upcoming BEV factory. Ford’s approach shows how legacy automakers are embracing first-principles engineering to compete in the EV space. This isn’t just a manufacturing upgrade—it’s a philosophical shift. Ford is betting $5 billion and reshaping its plants to make EVs simpler, cheaper, and more American-made. Source: https://lnkd.in/gmBwZcbK #FordEV #EVPlatform #AssemblyTree #GigaCasting #LFPBattery #EVManufacturing #ElectricVehicles #FutureOfMobility

Why do identical SiC devices perform differently in your EV power modules? The answer usually lies in overlooking the interconnected design of five critical components. Most EV power electronics engineers focus on the semiconductors. But here's what separates successful modules from failures: 𝗧𝗵𝗲 𝗙𝗶𝘃𝗲 𝗗𝗲𝘀𝗶𝗴𝗻 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 𝗘𝘃𝗲𝗿𝘆 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗠𝘂𝘀𝘁 𝗠𝗮𝘀𝘁𝗲𝗿: • 𝗠𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝘀 (𝗘𝗻𝗰𝗮𝗽𝘀𝘂𝗹𝗮𝘁𝗶𝗼𝗻) - Your module must survive 150°C temperature swings during real driving cycles. Design for extreme thermal variations from day one. • 𝗦𝘂𝗯𝘀𝘁𝗿𝗮𝘁𝗲 𝗦𝘁𝗮𝗰𝗸-𝘂𝗽 - Direct Bonded Copper substrates need proper thermal expansion matching. Mismatched coefficients create mechanical fatigue that kills modules prematurely. • 𝗚𝗮𝘁𝗲 𝗔𝘁𝘁𝗮𝗰𝗸 𝗗𝗲𝘀𝗶𝗴𝗻 - Use Kelvin connections to avoid feedback between control and power signals. Each parallel device needs its own balanced gate loop. • 𝗣𝗼𝘄𝗲𝗿 𝗟𝗮𝘆𝗼𝘂𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - Minimize parasitic inductances through symmetric routing. The cell/split concept reduces switching loop inductance significantly. • 𝗧𝗲𝗿𝗺𝗶𝗻𝗮𝗹 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 - Here's the shocker: terminals contribute up to 50% of your total parasitic inductance. Make them short and wide, with even numbers of pads for current balance. But how do you systematically approach this complexity? The methodology matters as much as the components. Start with target specifications including thermal requirements and EMI constraints. Then move through mechanical requirements, substrate definition, and component placement before tackling the routing challenges. 𝗧𝗵𝗿𝗲𝗲 𝗔𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗗𝗲𝘀𝗶𝗴𝗻 𝗥𝘂𝗹𝗲𝘀: 1. Design your mechanical constraints first - they dictate everything else 2. Balance thermal expansion coefficients across all substrate layers   3. Never underestimate terminal inductance in your power loop calculations The transition from Si IGBTs to SiC MOSFETs isn't just about swapping devices. It's about rethinking the entire module architecture for higher switching speeds and thermal performance. SiC devices switch faster, generating more EMI. They operate at higher temperatures, stressing mechanical joints. They demand lower parasitic inductances for optimal performance. Each design decision ripples through the other four pillars. Change your gate layout? It affects EMI and thermal distribution. Modify terminals? Power loop inductance shifts. Smart engineers treat power module design as a system optimization problem, not isolated component selection. What's been your biggest challenge when designing SiC power modules for EV applications? 𝗦𝗼𝘂𝗿𝗰𝗲: "Power module electronics in HEV/EV applications: New trends in wide bandgap semiconductor technologies and design aspects", Elsevier.

Step-by-Step Guide for Inverter Module Design and systems engineering for Traction Motor in EVs   System Engineering Design Step 1: Define System Requirements • Vehicle-Level Requirements: ◦ Voltage Range ◦ Power level (e.g., 50 kW to 250 kW) ◦ Cooling method (air or liquid) ◦ Safety and protection (ISO 26262, ASIL levels) Functional Requirements: ◦ Motor control (Field-Oriented Control - FOC) ◦ Torque/speed response time ◦ Regenerative braking ◦ Fault detection (short circuit, overvoltage, overheating) Non-Functional Requirements: ◦ Size, weight, cost ◦ Efficiency target (>95%) ◦ EMI/EMC compliance Step 2: Functional Architecture Definition • Define subsystem blocks: ◦ Power stage (IGBT or SiC MOSFETs) ◦ Gate driver circuit ◦ Current and voltage sensing ◦ Control board (MCU, DSP, FPGA) ◦ HV & LV power interfaces ◦ Communication (CAN, LIN) Step 3: Safety & Standards Compliance • ISO 26262 – Functional safety • ISO 21434 – Cybersecurity (if connected to VCU) • IEC 61851 / ISO 15118 – Charging interface coordination • Automotive EMI/EMC: CISPR 25, ISO 11452 • Thermal runaway mitigation and insulation standards (IEC 60664, 61140) Step 4: Control System Development • Motor control algorithms: ◦ Field-Oriented Control (FOC) ◦ Space Vector PWM (SVPWM) ◦ Torque and speed loops Sensor fusion: ◦ Resolver / Hall sensor integration ◦ Current sensors for vector control • Software-in-the-loop (SIL), HIL testing Hardware Design Phase Step 5: Power Circuit Design • Topology: 3-phase inverter (6-switch) using IGBTs or SiC MOSFETs • DC Link Capacitor Design: ◦ Rated for ripple current ◦ Film/ceramic or electrolytic • Snubber circuit: For voltage spike suppression • Current Sensors: Shunt, Hall-effect, or Rogowski coil Step 6: Gate Driver Circuit Design • Fast switching, isolated gate drivers • Fault protection (UVLO, overcurrent, desaturation detection) • Dead-time control and soft switching Step 7: Control Board (PCB) Design • Processor: Automotive-grade MCU/DSP (e.g., TI C2000, NXP S32K, Infineon Aurix) • Interfaces: ◦ CAN, SPI, UART, PWM ◦ Resolver/Hall interface • Power Supply: DC-DC converters (LV to 3.3V/5V rails) Step 8: Thermal Management Design • Heatsinks and/or liquid-cooled baseplate • Thermistors or RTDs for junction temperature monitoring • Thermal simulation (ANSYS, Simcenter) Step 9: EMI/EMC Filtering • Input/output filters (LC filters, CM chokes) • Shielding and grounding strategy • Layout optimization: minimize loop areas, use ground planes Step 10: Mechanical Integration • Connector types (HVIL, LV, signal) • Enclosure design (IP67/69 rated) • Vibration resistance (ISO 16750) • Mounting and serviceability Step 11: Prototype & Testing • Validation stages: ◦ Bench test (no load) ◦ Dyno test with PMSM motor ◦ Vehicle integration testing • Test cases: ◦ Full load, partial load ◦ High/low temperature ◦ Fault injection and safe state fallback Step 12: Documentation & Release

I’ve seen a lot of media coverage of this this week – manufacturers warning MPs that EV targets aren’t in line with consumer demand and we could see restricted sales of petrol cars – and therefore increased prices – as they seek to avoid prohibitive fines. This is particularly concerning for our 760,000 customers who rely on their vehicles for their independence.   But the story for me isn’t blaming industry or government targets, it’s why more isn’t being done to address the root cause which is the lack of demand for EVs. It’s a complex picture but at its core is that the switch to electric is not yet joined up or inclusive. The success or failure is measured by so much more than sales volumes, it’s the whole ecosystem and experience.   We have the largest vehicle fleet in the UK and a huge amount of lived experience and insight from our customers and their families. They are the EV drivers of the future and they include families without driveways or with lower household incomes or living in villages with fewer services. In short, they’re not the early adopters and company car users currently driving EV sales, they are representative of our wider population, and they tell us that the switch to electric isn’t working for them.   So it’s not about adjusting targets or restricting sales, it’s about understanding how to drive more demand and changing the public narrative. We have to collaborate - as industry, government, local authority, private business, tech and more – we have to listen to customers and we have to fix the pain points and barriers to widespread adoption, or we risk leaving a huge proportion of the population behind. 

Most people drive less than 40 miles a day. But when it comes to EVs, they want 400. Let’s talk about the most misunderstood number in electric vehicles: range. In the U.S., the average driver clocks about 35–40 miles per day. In the UK, it’s around 20–25. Even in Norway, where EVs dominate, daily usage rarely exceeds 50 miles. And yet across markets, drivers expect 300–400 miles of range (480–640 km) to feel “comfortable” switching to electric. In Norway, where 90% of new cars are electric, most buyers still prefer 400+ km (250 mi). In the UK, typical EVs offer about 211 miles, but drivers want 300+. In Germany and France, the average EV range is around 185 miles, yet consumers still ask for 250+. In China, many urban EVs offer about 140 miles, and sell in massive volume because the charging network supports it. In the U.S.? Most new EVs offer 250–300 miles, but buyers fixate on the mythical 400-mile “comfort zone.” So what’s going on? Range anxiety isn’t about logic, it’s about confidence. Even if most people only use a fraction of their battery each day, they want to know they could drive farther. And that’s where infrastructure, not just batteries, changes the game. The better the charging network, the less people obsess over max range. Bottom line is, if we want mass adoption, we need to stop chasing oversized batteries and start investing in fast, visible, reliable charging. Because the real range problem isn’t how far an EV can go, it’s how far people think they’re allowed to. #EVs #RangeAnxiety #EVStrategy #CleanTech #Mobility #ElectricVehicles #EVCharging #EnergyTransition #BatteryTech #EVInfrastructure

Both SiC and GaN are poised to play a central role in the future of automotive power electronics, transforming the NEV industry and contributing to its rapid growth. 🔘 Growing Adoption of SiC and GaN in the Automotive Industry: - SiC is becoming a key technology in EVs, with notable models such as EXEED STERRA ES, AION V, BYD Seal, and ZEEKR 007 adopting SiC technology. - GaN is also making progress, especially in OBCs and automotive LiDAR, with companies like Infineon and EPC leading the charge. 🔘 SiC Power Devices in NEVs: - SiC’s widespread adoption is supported by international semiconductor giants such as STMicroelectronics, Infineon, and onsemi, which hold a technological and market advantage. - The Chinese NEV market is experiencing explosive growth, prompting international players to invest heavily in local partnerships to expand their presence, such as STMicroelectronics' collaboration with San’an Optoelectronics for localized production. 🔘 Technological Advancements and Cost Reduction in SiC: - SiC power devices are becoming more efficient and cost-effective due to technological advancements like Infineon’s new SiC trench gate MOSFET technology, which improves performance by 20%. - SiC production is shifting from 6-inch to 8-inch wafers, which will further reduce costs and increase efficiency, promoting its broader application in mid-to-low-end NEVs. 🔘 GaN’s Growing Role in Automotive Applications: - While GaN is still in the early stages of adoption in automotive scenarios, it is showing promise in automotive LiDAR systems, OBCs, and DC-DC converters. - GaN’s high efficiency, fast switching speeds, and smaller footprints make it ideal for low-voltage (sub-400V) automotive applications, with future potential for high-voltage GaN devices, such as Bosch’s 1200V GaN technology. 🔘 Strategic Partnerships and Investments: - STMicroelectronics partnered with Great Wall Motors, Infineon with Xiaomi, and onsemi with Li Auto. These collaborations aim to reduce supply chain costs, ensure capacity, and increase market shares in China’s booming NEV sector. 🔘 Future Trends and Market Growth: - The transition from 400V to 800V systems in NEVs is accelerating, with SiC power devices playing a critical role in improving charging speed, motor efficiency, and battery performance. - SiC’s role in 800V platforms is becoming a standard in the latest NEV models, contributing to the overall growth of the NEV market. - GaN devices, although currently limited to sub-400V applications, are expected to penetrate main drive inverters by 2030. Reference Source: https://lnkd.in/dHr6nAFm The Future of Automotive: Setbacks and Progress, https://lnkd.in/dAb6zxrv

A strong second-hand market for electric vehicles might be the most underrated catalyst for accelerating EV adoption. I always believed this in theory, but it became even clearer after my own recent experience buying a used EV. I just bought a 4-year-old EV with 45,000 km. Excellent condition, drives like new, and the price was 55% lower than when it was new. At first, I thought I had found a unicorn deal. But then I realised it wasn’t a one-off: most used EVs are selling at massive discounts. ❓ Why? After speaking with several people in the sector, the pattern became obvious: 1️⃣ Many buyers still fear battery degradation 2️⃣ Others worry the technology evolves so quickly that a used EV becomes obsolete too fast These concerns keep prices low, even when the product is excellent. ❗ After a decade working in electric mobility, I felt confident buying used and the truth is many of these fears are outdated: 🔋 Battery health today is easy to check with independent diagnostics. Real-world data shows that at 50,000 km most EVs lose almost no meaningful range. Most OEMs offer 8-year battery warranties. Full battery replacements are rare and usually only relevant after extremely high mileage, often above 500,000 km, at which point ICE cars need major repairs too. 💻 Technology risk exists, but it’s manageable. Yes, some early EVs only make sense at deep discounts. But many models remain competitive for years: EVs with 75 kWh batteries, 400-V systems above 150 kW charging speeds, or 800-V platforms. Teslas, Hyundai and others often sell at 50% or more below their original prices while still delivering top-tier performance. And the reality is that EVs of the next 10 to 15 years will not be radically different from these in everyday use. The 500km range we can find today is aligned with ICE vehicles and the charging speed is already very high in some models. ‼️ For buyers, this arbitrage is great news. For the industry, it’s a problem. The second-hand market is 4-5x larger than the new-car market. If consumers don’t trust used EVs, the entire ecosystem suffers. A healthy used market is essential for affordability and for accelerating adoption. And once people try an EV, they rarely go back to combustion. Moreover, there is almost no fiscal incentives exist for second-hand EVs. This is a major policy gap that could really have a positive impact on the secondary market. And here’s the counter-intuitive part: higher second-hand EV prices actually help sell more new EVs. Most new cars are sold through long-term leases. Leasing depends on residual values: 1️⃣ Low second-hand prices lead to low residuals, which lead to higher monthly payments, making new EVs harder to finance. 2️⃣ Stronger second-hand prices increase residuals, lower leasing costs and help sell more new EVs. A trusted, liquid second-hand market is the foundation of a scalable EV industry. Happy to chat with anyone considering buying a used electric car.

🔌 Europe does not have an EV rejection problem. It has a transition-friction problem. That friction is now showing up in the data. Recent European Pulse / POLITICO polling shows that 58% oppose the 2035 ban on new combustion cars. At the same time, 65% support more public funding for public transport, even if that means higher taxes. That is not a trivial contradiction. It suggests Europeans are not simply rejecting cleaner mobility. They are pushing back against a transition that still feels costly, awkward, and uneven in practice. The EAFO Consumer Monitor 2025 points in the same direction. European drivers are not broadly anti-EV. Attitudes are often more neutral than polarised, and the real drop-off comes at a much more practical question: is a BEV actually workable for me? That is not resistance. It is rational hesitation. Because once you move from sentiment to practicality, the economic tension becomes obvious. Consumers expect a BEV at around €20,000. At the same time, expected range remains high, commonly 400 to 600 km. That is not ideology. That is a product, affordability, and confidence gap. And there is a second layer. The transition does not arrive under the same conditions for every household. Housing, parking, and charging access still shape how easy, how convenient, and how economical the switch actually feels in daily life. That matters strategically. Under ICE, the system was relatively simple: one refuelling logic served almost everyone. With electrons, mobility runs on a charging ladder: home, workplace, on-street, destination, and fast charging. The real policy task is to make sure that ladder is not easy for some households and steep for everyone else. Because policy can set targets. But it cannot force mass adoption if too many mainstream customers still experience the transition as financially unclear, operationally awkward, or simply better suited to someone else’s circumstances. So I think Europe’s EV debate is slowly changing. Less a pure technology question. Less a simple pro-EV vs anti-EV argument. More a question of whether electrification works on ordinary terms, at ordinary cost, under ordinary living conditions. That is why the real challenge is no longer just building better electric cars. It is reducing the friction between climate ambition and everyday feasibility. Europe will not win this transition by targets alone. It will win it when electrification works not just for the early adopter, or the homeowner with a driveway, but for the wider middle of the market. That is the harder challenge. But now it looks increasingly like the real one. P.S. Taking Michael Liebreich's excellent advice, I am officially releasing this Charging Ladder 1.0 framework under a Creative Commons CC BY 4.0 license. You are free to share, use, and adapt this framework, provided you credit Tamas GABOR . #EVs #EnergyTransition #Mobility