Optimum Matching of Electric Vehicle Powertrain

AbstractOptimum matching of a target vehicle powertrain was formulated as a nonlinear constrained optimization problem. The dynamic and economic objective functions were respectively set up by maximum grade ability and driving range. In addition, the simulated annealing genetic algorithm (SAGA) was used to solve the optimum problem. In order to evaluate the effects of the optimized powertrain on vehicle performance, simulation models of the target and optimized vehicles were established in CRUISE software and verified by test results. It is helpful to achieve dynamic performance improvement, energy consumption reduction and driving range increase