Optimized Energy Control Scheme for Electric Drive of EV Powertrain Using Genetic Algorithms

Automotive applications often experience conflicting-objective optimization problems focusing on performance parameters that are catered through precisely developed cost functions. Two such conflicting objectives which substantially affect the working of traction machine drive maximizing its speed and minimizing energy consumption. In case an electric vehicle (EV) powertrain, is bounded by battery dynamics (charging capacity) depend consumption voltage current caused driving cycle schedules, traffic state, EV loading, temperature. other words, depends upon A conventional control technique improves at However, proposed optimized (OEC) scheme optimizes this using robust linear parameter varying (LPV) tuned genetic algorithms significantly powertrain performance. The analysis OEC conducted simulator MATLAB/Simulink based simulations as well induction platform. accuracy quantitatively assessed to be 99.3% regarding elaborated speed, voltage, results against standard cycles.