Study on Parameter Matching Optimization of City Bus Power System Based on Operating Conditions

The operating conditions of typical city lines in Xi'an were measured by GPS equipment. The transient condition and modal condition were constructed by using cluster analysis method and multi-objective optimization theory. Based on the developed conditions and the actual road demand power and prototype parameters, the motor and battery selection were completed. Then parameters of motor, battery, and drivetrain can be reasonably matched. Drivetrain parameters were used as optimization variables. A mathematical model was established for the economical efficiency of the entire vehicles . Simulated annealing particle swarm optimization algorithm was used to optimize the speed ratios of the drivetrains. CRUISE software was utilized to establish vehicle simulation model. Then simulation calculations are implemented through the design of dynamic and economical calculation tasks. The simulation results show that the vehicle dynamic performance meets the design requirements before and after optimization, and the cruising range increases by 1.71 km under the optimized cycle conditions.