Research On Energy Management Strategy Optimization For Series-parallel Hybrid Electric City Bus

Since hybrid electric vehicle combines the advantages of both conventional vehicle and electric vehicle,it has the best prospect at present.Facing the dynamic system with multiple power sources,it is of great significance to size the parameters of the components and to design a feasible energy management strategy.In this paper,coaxial series-parallel hybrid electric city bus is used as the case study.According to the parameters of vehicle,the performance targets and the typical driving conditions of city bus,the parameters of the components are determined by the characteristic driving condition analysis and the typical driving condition analysis.The main modes are determined based on the configuration characteristics of hybrid electric system.The ISG starting engine mode is introduced to simulate the starting process of engine.The clutch closing control mode is proposed to improve the ride comfort when the clutch is closed.Considering the constraints such as braking regulations,a parallel regenerative braking strategy is developed based on the existing mechanical braking system.Correction factors are introduced to improve ride comfort of braking process.Energy management strategy is designed based on driving state and braking state.The simulation model is built based on Cruise,and the forward simulation is carried out.The dynamic simulation results show that vehicle dynamic performance meets the design requirements,and the results of parameters matching are reasonable.The mode switching logic aligns with expectations according to mode switching process.The economic simulation results show that the driving range and economic performance meet the expected requirement.The SOC of battery can be maintained at the low level,which indicates that the charge-saving capacity of the energy management strategy is feasible.Genetic algorithm is used as the optimization algorithm,and the crossover probability and mutation probability changing with evolutionary generation and population adaptability are proposed to improve the convergence speed and search quality.The joint simulation model and improved genetic algorithm are combined to establish the parameters optimization model of energy management strategy.The energy management strategy parameters are optimized for Chinese typical city bus driving cycle and composite driving cycle respectively.The results show that the economic performance after the optimization has been improved in different degrees.And the parameters obtained by optimizing for the composite driving cycle have a better adaptability to driving cycles.