Study On Parameter Optimization And Control Strategy Of Hybrid Energy Storage System For Electric Vehicle

With the increasing demand for energy and the emerging of environmental problems,electrification has become an important direction for the development of automotive industry.Nowadays,with the vigorous development of electric vehicles,power batteries as energy sources still have some problems such as low power density and insufficient cycle life,which restrict the further development of electric vehicle technologies.The hybrid energy storage system combines the power battery and ultracapacitor to form an electric-electric hybrid system to meet the needs of vehicle energy density and power density for energy storage device,which provides a possible solution to solve the current battery technology bottleneck.In this thesis,the hybrid energy storage system of electric vehicle is taken as the research object.In order to achieve its optimal performance,the research is carried out around parameter optimization and control strategy.The main research contents are as follows:Firstly,the working characteristics of the power battery,ultracapacitor and bidirectional DC/DC converter of the hybrid energy storage system are analyzed to clarify their performance under different working conditions.Based on the equivalent circuit model,the characteristics of battery and ultracapacitor are showed and modeled,and the bidirectional DC/DC converter is modeled according to its efficiency characteristics.Considering the influence of battery capacity fading on parameter optimization,a semi-empirical battery life model based on experimental data is established.Finally,the performance of the hybrid energy storage system with different topologies is compared to determine the system topology.Aiming at the parameter optimization of the hybrid energy storage system and control strategy,a system parameter design method based on multi-objective optimization algorithm is proposed.Taking the cost and energy consumption of the hybrid energy storage system as the optimization objective,the logical threshold control strategy is adopted.On the premise of ensuring the energy demand and power demand of the vehicle,the grouping of batteries and ultracapacitor and the logic threshold of the control strategy are constrained.The parameter optimization of the hybrid energy storage system is implemented based on the strength Pareto evolutionary algorithm SPEA2.SPEA2 implements the joint optimization of system parameters and strategy parameters by using the Simulink model of the hybrid energy storage system in real time,and obtains a set of non-dominated optimal solutions.Finally,the evaluation index is adopted to determine the optimal parameter configuration of the hybrid energy storage system.Considering that the rule-based logic threshold control strategy can not deal with complex road situation,there is a suboptimal problem in practical use,which can not give full play to the advantages of the hybrid energy storage system,a real-time control strategy based on convex optimization and BP neural network prediction is proposed.Making the non-convex optimization problem convexification,and convex optimization based on global condition information for three typical driving cycles is carried out,so as to obtain the optimal power distribution at each time and summarize their power distribution rules.The results of convex optimization are used as data samples for off-line learning by BP neural network.And the prediction results are compared with the convex optimization results.It is found that the prediction performance of BP neural network in vehicle braking energy recovery has some shortcoming.Based on the previously summarized power distribution logic,the control strategy based on BP neural network prediction is improved,and the logic discrimination and power distribution strategy in the case of braking energy recovery are introduced.Finally,by constructing the unknown driving cycles,it is verified that the improved control strategy can give full play to the advantages of energy source and has good performance.The research aims to provide theoretical support for the optimal design and control of hybrid energy storage system in electric vehicles,and also forms the foundation for the practical application of hybrid energy storage system in electric vehicles.