Research On Instantaneous Optimized Energy Management Strategy Of CVT Parallel Hybrid Electric Vehicle

Hybrid electric vehicles(HEVs)can not only make up for the shortcomings of high fuel consumption and high exhaust emissions of ordinary fuel vehicles,but also make up for the short range of pure electric vehicles,which is a hot spot in automotive research.How to reasonably match the parameters of the power transmission system and coordinate the power distribution between the engine and the motor during driving will directly affect the fuel economy and emissions of the vehicle.As the core technology of HEVs,the formulation of energy management control strategies is the focus and difficulty of current hybrid vehicle research.For hybrid vehicles equipped with CVT,how to achieve the matching between CVT speed ratio and power source directly affects the overall performance of the vehicle.Therefore,this paper studies the instantaneous optimized energy management strategy of CVT parallel hybrid electric vehicles in combination with the national key research and development plan projects undertaken by the research group.The specific research contents are:(1)On the basis of existing CVT parallel hybrid vehicles,the power source parameters are matched according to the vehicle’s power performance;The numerical models of each component were built based on the Matlab / Simulink platform;Based on the vehicle’s longitudinal dynamics equation,the vehicle dynamics simulation model was built;Based on the PID control algorithm,a driver model was established which uses throttle opening to calculate the vehicle’s required torque.(2)The research content of this paper is based on the Equivalent fuel consumption minimization strategy(ECMS).Aiming at the problem that the traditional ECMS strategy cannot fully utilize the electric energy when the battery SOC is higher or lower than the target value,a three-dimensional function is established with the battery SOC and the vehicle acceleration as independent variables,and the equivalent factor correction coefficient as the dependent variable.The correction function was optimized by genetic algorithm.The vehicle’s forward simulation model was established to verify the improved control strategy.The simulation results verified the feasibility of the improved ECMS control strategy.(3)Although the ECMS has better fuel economy,its driving conditions are more sensitive to the equivalent factors.The selection of equivalent factors under actual driving conditions cannot guarantee the best,and the battery SOC cannot be maintained well.Therefore,the strategy is less robust.Rule-based control strategies often use SOC as a limit when formulating mode switching rules.Therefore,rule-based control strategies have better battery SOC retention performance and are not affected by driving conditions.The determination of the speed ratio of a hybrid vehicle equipped with a CVT transmission directly affects the fuel economy of the vehicle.Based on this,this paper uses an improved ECMS strategy to optimize the CVT speed ratio,and nests the optimized CVT speed ratio in a rule-based controller to form a control strategy based on a combination of ECMS and threshold values.Based on the platform of Matlab /Simulink to build the vehicle back simulation model verification,the simulation model is verified and compared with the CVT speed ratio optimized under the instantaneous efficiency optimization strategy.The results verify that the optimized CVT speed based on the improved ECMS strategy has a better effect on vehicle fuel economy and SOC retention.(4)The road conditions of the vehicle during the actual driving process are random and changeable,and each driving condition has its optimal CVT speed ratio.If the CVT is not selected properly,it will directly affect the fuel economy of the vehicle.In view of the above problems,build a road condition recognition model to select the CVT speed ratio.Select the characteristic parameters and use K-means for cluster analysis of driving conditions,and use the improved ECMS strategy to optimize the CVT speed ratio under each working condition.Establish a working condition identification model which is based on Euclidean closeness.The best CVT speed ratio is selected based on the identified operating condition.The simulation uses a combination of WLTC and NEDC,which are more in line with the actual driving of the car.The results show that,compared with the CVT speed ratio obtained from the optimal strategy of instantaneous efficiency and the CVT speed ratio obtained without identification of operating conditions,the CVT speed ratio obtained based on operating condition identification strategy proposed in this paper,while maintaining the battery SOC,the fuel economy has increased by 1.36% over the strategy without identification of operating conditions,and 2.02% over the optimal strategy for instantaneous efficiency.