Research On Adaptive Cruise Control Strategy Of Electric Vehicle Considering Battery Degradation Characteristics

The advancement of technology and the development of society have prompted today’s automobile industry to move towards electrification,intelligence,and networking.Pure electric vehicles are a rapidly developing new type of vehicle in recent years.Compared with traditional fuel vehicles,they have the advantages of low noise,zero emissions,and low-carbon environmental protection.However,their development also faces bottlenecks.This thesis aims to address the issues of limited range and significant battery capacity attenuation for electric vehicles.It focuses on a pure electric vehicle with Adaptive Cruise Control(ACC)function and proposes an adaptive cruise control strategy that considers battery capacity decay characteristics.The purpose is to improve the driving economy of the vehicle while reducing the impact of battery capacity decay on vehicle performance.The research work conducted and the achievements obtained are as follows:(1)Analysis of lithium-ion battery degradation mechanism and construction of capacity degradation model.The degradation mechanism of lithium-ion batteries is studied and the factors affecting battery performance degradation are analyzed,including Depth of Discharge(DOD),discharge rate,and ambient temperature.The test conditions of lithium-ion battery monomers under different DODs,discharge rates,and ambient temperatures are designed based on the actual driving conditions of vehicles.The capacity data obtained from the tests are fitted with an exponential function curve using nonlinear least squares to obtain a semi-empirical model that can characterize battery capacity loss.(2)Construction of vehicle system dynamic model and adaptive cruise control model.The established system dynamic model includes the vehicle longitudinal dynamic model,motor model,and battery model.The variables in the longitudinal dynamic model are set according to the structural parameters of pure electric vehicles,the motor model is established based on the data obtained from the dynamometer experiment,and the battery model is established based on the actual parameters of the battery.The Ohmic internal resistance in the model will be adaptively updated with the decay value of the battery capacity.The adaptive cruise control model includes the cruise mode and follow-up model,both of which are established based on the state space equation.The vehicle’s state variables,such as speed and acceleration,are calculated by the vehicle system dynamic model.In the distance tracking of the follow-up model,a fixed distance tracking model that takes into account both driving safety and road traffic efficiency is designed instead of a variable headway distance.(3)Design of adaptive cruise control strategy considering battery capacity degradation characteristics.Based on the Model Predictive Control(MPC),an optimized tracking and comfort MPC1 controller is designed.The battery capacity degradation model is introduced as the economic evaluation index to achieve comprehensive optimization of the vehicle’s driving process.MPC2 controller with fixed weight and adaptive weight AMPC controller optimized by fuzzy logic control that can adapt to the vehicle’s driving conditions are designed according to the weights of different performance.The Proportional-Integral and Derivatice(PID)and Sliding Mode Control(SMC)controllers that do not consider battery aging characteristics are designed to achieve distance and speed tracking of the vehicle.(4)Validation of the effectiveness of the adaptive cruise control strategy based on the model in the loop and hardware in the loop.The validity of the vehicle’s strategy under typical operating conditions is verified based on the MATLAB/Simulink environment.The effectiveness of the proposed adaptive cruise control strategy considering battery capacity degradation characteristics is validated through software simulation testing.The results show that compared with the fixed weight MPC2 controller,traditional PID,SMC and MPC1 controller,the AMPC controller designed by fuzzy weight can better adapt to working conditions,effectively reduce the rate of battery capacity decay and improve driving economy.The validation of the proposed control strategy is completed based on the hardware in the loop platform,demonstrating its effectiveness and real-time performance.