Nishiraj Mane

Introduction AI-driven generative design is revolutionizing automotive part development by exploring massive design spaces automatically. Instead of starting from a preconceived shape, generative design takes high-level goals (weight, strength, material, cost, etc.) and uses AI algorithms to propose hundreds of valid design variants that satisfy those constraints. In practice, engineers specify loads, fixations, materials and manufacturing methods, and the software generates optimized geometries. This technology is especially useful in automotive applications where weight reduction and performance are critical. For example, lighter vehicle components directly translate into better fuel economy and longer electric range. A recent case study showed that a generatively designed engine-mount bracket achieved a 30% lower weight than the traditional design (with higher rigidity), resulting in a 2.8 km increase in electric range and 3.5 g/km reduction in CO₂ emissions. Automakers...

Overview: Regenerative braking is a key technology in hybrid and electric vehicles (EVs) that recovers kinetic energy during deceleration by running the traction motor as a generator. This recovered energy, which would otherwise be wasted as heat in friction brakes, is stored in the vehicle’s battery or capacitor for later use. The fundamental principle relies on electromagnetic induction – as a motor’s rotor continues to spin faster than the magnetic field it creates (or is forced to spin), it generates an opposing electromotive force (back-EMF) that can drive current back into the energy storage system. In effect, the motor–inverter acts as a generator during braking. Regenerative braking can significantly improve vehicle energy efficiency (recovering a substantial fraction of braking energy) and reduce mechanical brake wear. However, its performance and characteristics depend heavily on the type of electric motor used, the power electronics and control strategy, and system co...