Research On Multi-objective Optimization Energy Management Strategy Of DHT-equipped Hybrid Electric Vehicle

Energy conservation,environmental protection,safety and intelligence are the development directions of the modern automobile industry in response to the requirements of sustainable development.Dedicated hybrid transmission(DHT)is a mainstream technology that can highly couple the operating characteristics of the engine and the motor to maximize powertrain performance.DHT-equipped plug-in hybrid electric vehicles have obvious fuel-saving advantages,but their structure is more complex.The key to give full play to their advantages is to establish reasonable energy management strategies to coordinate and optimize engine and motor power distribution.At the same time,power battery occupies an important part of the acquisition cost of PHEVs,but most of the current energy management strategies only consider fuel economy,ignoring the rapid decay of battery life resulting in an increase in the overall driving cost and a shortened service life of the vehicle.Therefore,based on a DHT-equipped plug-in hybrid electric vehicle,the rule-based and optimization-based energy management strategies were respectively established in this paper.Battery life attenuation was introduced into energy management strategies for quantitative analysis,and a multi-objective optimization energy management strategy considering battery life was established.The main research contents are as follows:Firstly,according to the research object of this paper,the main characteristics of vehicle structure,power system configuration,operational mode and energy flow under each mode are analyzed.Based on the target dynamic performance index,the parameters of engine,motors,power battery and speed ratio of each transmission gear are matched according to the longitudinal dynamics of the vehicle.The experimental modeling method was used to establish a simplified numerical model of power components for energy management on MATLAB/Simulink platform.The simulation analysis proved that the matching results met the dynamic performance indexes.Secondly,a widely used rule-based energy management strategy was established.The mode division rules based on battery state of charge(SOC)were determined,and the vehicle operating mode was divided into pure electric mode,charge depleting mode and charge sustaining mode.At the same time,the power distribution rules of the vehicle under different operating modes were determined,the logic threshold values of mode division were set,the control effect is simulated and analyzed,and the hardware-in-the-loop(HIL)was used for verification.Then,in order to solve the problem that the rule-based energy management strategy depends on engineering experience and cannot reach the optimal,the adaptive equivalent consumption minimum strategy(A-ECMS)for PHEVs is established based on Pontryagin’s minimum principle.The penalty function is introduced and the PI controller is used to adjust the equivalent factor adaptively,so as to improve the control ability on battery SOC and the adaptation ability to cope with changing conditions.In addition,the engine torque fluctuation limit is introduced.By converting engine torque fluctuation into equivalent fuel consumption,the frequent engine torque fluctuation under the ECMS energy management strategy is effectively limited,and the working efficiency of the vehicle is further improved.Finally,the structure,life attenuation mechanism and main influencing factors of life attenuation of lithium-ion batteries were analyzed,and the battery capacity attenuation was determined as the evaluation index of cycle life attenuation.A semi-empirical model of battery capacity attenuation was established based on the battery life attenuation test data.Through comparison,the model data were in good agreement with the test data.The model is proved to be accurate in predicting battery life.The battery capacity attenuation model is introduced into the energy management strategy to establish a multi-objective optimization energy management strategy considering battery life.The pattern search optimization algorithm was used to optimize the control parameters,and the comprehensive equivalent fuel consumption was reduced by 4% after optimization.By comparing and analyzing the control effects of the three strategies through simulation,it is determined that the multiobjective optimization energy management strategy is the one with the lowest comprehensive use cost,which is 5% and 10.9% lower than A-ECMS and rule-based control strategy respectively.