Optimization Of Hybrid Electric Bus Control Strategy With Virtual Development Platform

With the increase of environment problems and energy consumption, Hybrid-Electric Vehicle (HEV) offers an effective way to solve reducing fuel consumptionand automobiles emission problem, which is one of the developing tendencies ofautomobile industry. As the core technique of energy distribution, the control strategybecomes one of the focuses and the hot point of HEV. In order to development andoptimization of Hybrid Electric Bus(HEB), the virtual development platform wasdesigned and control strategy was developed based on this platform.Control strategy development method for V cycle has been studied. Throughcomparative and analysis of the advantages and disadvantages for V cycle, the virtualdevelopment platform——platform for control strategy optimization of electric buswas developed, which can realize simulation, optimization and Rapid ControlPrototype(RCP) test.HEB simulation model was built based on the forward simulation model in AVLCRUISE, and verified by whole model validation.Working mode and road conditions for HEB has been studied. High efficientWorking range of the engine and mode of braking energy recovery was determined,and drive and braking torque were distributed. Power analysis control strategy wasbuilt in component of control strategy development based on the virtual simulationdevelopment platform. Simulation was made to test the control strategy.The advantages and disadvantages of optimization algorithm had been studied.The algorithm combines simulated annealing algorithm (SA) and NLPQL is proposed.Comparing Different optimize frequency with SA and the combined algorithm undertypical city-bus driving-cycle in China. Simulation results show that the combinedalgorithm improve the search efficiency and the calculation quality.Through vehicle optimized simulated platform of driver in the loop, RCP test has been completed. Test results show that the virtual simulation development platformsatisfy test vehicle performance requirements, the optimal control strategy arereasonable and satisfy the vehicle performance.