Research On Adaptive Cruise Control Strategy For Electric Vehicle Based On MPC

With the development trend of vehicle electrification and intelligentization,the technology of vehicle intelligent assisted driving has become a research hotspot in the industry and has been widely used.As a key part of the intelligent assistant driving system,the adaptive cruise system can effectively reduce the driving intensity of the driver and improve the safety of the vehicle.This article depends on the key research and development project of Ministry of Science and Technology project "the vehicle intelligent control and performance improvement technology",combined with a certain type of pure electric commercial vehicle intelligent product development and technical application requirements,aiming at the problem that the current adaptive cruise system does not fully consider the comfort and fuel economy,and studies the adaptive cruise control strategy of the electric vehicle with the goal of considering the vehicle's following ability,safety,comfort and economy in the cruise process.This paper firstly analyzes and summarizes the research status of the adaptive cruise control strategy at home and abroad.Based on the hierarchical control structure,the overall architecture of the adaptive cruise control strategy in this paper is designed,the control target of the upper decision algorithm and the lower control algorithm is analyzed,the main technical route of this paper is determined,and the dynamic model of the target vehicle is analyzed and constructed.Based on the dynamic system configuration and dynamic characteristics of the target vehicle,an adaptive cruise control algorithm is designed.The vehicle inverse longitudinal dynamics model is established,and the driving and braking mode switching strategy based on threshold is adopted to avoid frequent switching of driving and braking during cruise.The parallel braking energy recovery control strategy is selected to realize the braking energy recovery.On the basis of the above,a feedforward and feedback adaptive lower control algorithm for cruise system is designed,and the effectiveness of the lower control algorithm is verified under the typical acceleration signal input.Based on model predictive control theory,an adaptive cruise multi-objective optimization upper level decision algorithm is designed.The four aspects of economy,following ability,safety and comfort are selected to design the performance indexes and system constraints.The feedback mechanism is introduced to correct the prediction model,and the vector relaxation factor is extended to solve the feasible region,finally the constraint optimization problem is transformed into a standard nonlinear programming problem for solving.Finally,the control strategy model of the adaptive cruise system was built under the MATLAB / Simulink simulation platform,and five typical working conditions were selected for simulation,such as cruise at fixed speed,following cruise,stop-and-go of front car,cut-in of front car,and departure of front car.The results show that the adaptive cruise control strategy proposed in this paper has a good control effect in terms of followability,safety,cruise mode switching and response,and verifies the applicability and effectiveness of the control strategy.