Optimization Of Energy Management And Transmission Parameters For Parallel Hybrid Vehicle Based On Dynamic Programming

The hybrid vehicle is one of the important choices to develop the new energy strategy in our country,and the discussions about how to optimize its energy management strategies and parameters to improve the power performance and fuel economy have never come to an end from the moment it came into the public vision.But how to obtain the optimal control strategy and parameters at the same time,and extract rules from the optimal strategy to apply to the real vehicle controller,there are few studies related to these aspects.Based on the above two points of view,the thesis aimed at improving the fuel economy of a parallel hybrid vehicle,and obtained the following achievements:Firstly,the main components of the power system such as engine,motor,battery and so on were selected and matched based on the design requirements of the vehicle.The thesis built the control strategy model in Simulink environment,while the other components models were established in GT-DRIVE.In order to provide a reliable verification environment for the following control strategy optimization,the MATLAB-GT co-simulation platform was built to conduct a preliminary debugging for the vehicle model.Secondly,the Dynamic Programming(DP)algorithm was applied to solve the vehicle optimal control strategy,and the algorithm was verified under the NEDC driving condition.Furthermore,the Particle Swarm Optimization-Dynamic Programming(PSO-DP)algorithm was programmed to conduct the collaborative optimization of transmission ratios and torque distribution strategy for the hybrid vehicle.The calculation results show that,before the transmission ratios were optimized,the vehicle's fuel consumption per hundred kilometers was 4.59L/100 km under the NEDC driving condition.After the transmission ratios were optimized,the fuel consumption of the vehicle was reduced to 4.36L/100 km,and the fuel saving rate was 5.01%.Thirdly,for the preview of the driving conditions,the optimal control strategy calculated by the DP can't be applied to the online vehicle controller directly.In order to make the best use of the optimal strategy to revise the traditional control strategy,the rules extracting methods were put forward in three aspects: the boundary lines for mode-switch,torque distribution ratios and fluctuation range for SOC.The simulation verification was conducted based on the optimal transmission ratios calculated by the PSO-DP and the traditional control strategy optimized by the extracted rules.The simulation results show that in the premise of maintaining the balance of battery SOC,the fuel consumption per hundred kilometers was 4.73L/100 km with the optimized control strategy,17.2% less than the fuel consumption with traditional control strategy which was 5.71L/100 km.What's more,the fuel consumption was reduced to 4.36L/100 km after the cooperative optimization of control strategy and transmission ratios,which was 23.6% less than that before optimization.The simulation results show that the collaborative optimization algorithm can obtain the optimal control strategy,the method which applies the extracted rules to optimize the traditional control strategy and transmission parameters has significant effect on decreasing the vehicle fuel consumption,and provides a theoretical basis for the optimization of online vehicle energy management strategy and transmission parameters.