Energy Management Of Heavy Offload Hybrid Electric Vehicle

In order to improve the performance of heavy offload hybrid electric vehicle equipped with automated manual transmission(AMT),the energy management of single-axle parallel hybrid electronic system is analyzed and modled.Based on the analysis of the design requirements of the vehicle,the engine is matched,which is varifed of rationality by backward simulation of the vehicle's dynamic and economic performance.The simulation model of heavy offload hybrid electric vehicle is constructed through Cruise software.Then the design is inverted into dynamic programming(DP),and solving flow and factors of DP are extracted.A vehicle backward simulation is needed to design to embed the DP.DP is amended to improve the speed of operation,and the influenced parameters of DP are also optimized.On this basis,the optimal decisions and states,which can be used to extract logic threshold of online energy management,are obtained.To obtain road information for better optimizations,least square is designed to estimate generalized road resistance.To reduce the impact of early data,the RLS algorithm is amended.Besides,a correction method,which is to reduce the influence of the abnormal data,is proposed as well.The results of simulation and real vehicle tests show that the quality of the estimation of the generalized road resistance is improved by using the amended RLS algorithm,and the impact of the abnormal data is reduced as well.After getting the threshold and shift schedule used to determinine whether needs changing the mode and the gear,the online energy management algorithm is designed,which is varifed of rationality by co-simulation with Matlab and Cruise.