The Parameter Matching And Optimzation Of Power Source For Parallel Hybrid Electric Bus

Environmental pollution and energy shortage have been the difficulty in the sustainable development of China’ automotive industry and also restrict the development of global automotive industry. Hybrid electric vehicles(HEV), incorporating the advantages of traditional internal combustion engine vehicles and pure electric vehicles, can achieve the purpose of energy conservation and emissions reduction and has been the research hotspot in the field of new energy vehicles. The research object of this paper is a single shaft parallel hybrid electric bus while the parameter matching and optimization of power source is mainly discussed on.Powertrain component sizing is one of the key technology of hybrid electric vehicle development and power source including engine, motor and battery are the key component of powertrain, so reasonable parameters of power source can effectively improve the vehicle’s power, economy and emission performance. Since component matching is a multi-variable and multi-objective optimization problem, the best parameters will be achieved only after repeated calculation on the basis of accurate and complete simulation model. At the same time, different design goals are conflicting, which results into another question that how to coordinate the component parameters so as to weigh the different design goal. In addition, the vehicle performance is closely related to the control strategy parameters,so matching results under fixed control strategy parameters only are local optimum.In order to achieve the global optimal, the influence of the control strategy parameters must be fully considered.To solve above difficulties, a method applied to powertrain component sizing of HEV is proposed in this paper and it can realize parameter optimization automatically, obtain perfect matching result according to the weighted design target and realize the global optimal by concurrent optimization for component parameters and control parameters.The main contents are as follows:Firstly, parameters matching platform achieving optimization automatically is established based on Matlab/Simulink + Isight software in accordance with the characteristics of repeated calculation, coordinatetion and verification for parameters matching. The plant model including the engine, motor, battery, transmission, the longitudinal dynamics and the controller model are established in Simulink while numerical values of dynamic performance are carried out in Matlab and multi-island genetic algorithm with fast and random search ability is integrated into Isight software. After Isight obtaining performance values by calling Matlab/Simulink software and giving next design variable values automatically, the optimum matching results are converged through continuous iterative.Afterwards, paremeter matching of power source is carried out aimed at the optimal economy and the results show that the platform can realize automatic optimization, so it can be used as the research platform.Secondly, for weighing the different design goals, a multi-objective matching method is proposed. With the design goals of economy and downsize, the optimal matching results are determined througth setting weights for different object into a single objective.Then the NSGA-II algorithm is applied for Pareto solution through that any optimal matching results under different weighting can be found, which proves validity and superiority of the method.Further, considering dynamic performance as a design goal, and not just the constraint conditions, multi-objective matching results for fuel consumption, power performance and downsize are got, which expanding designer’ selection space.Finally, concurrent optimization of component parameters and control strategy parameters is done for the global optimal results, in which extracted key parameters of energy management strategy and component parameters combined as design variables.Then CRUISE software is applied for simulation analysis to local and global optimal matching results, the results show that the global results obtain more improvement.