Research on adaptive cruise control strategy of pure electric vehicle with braking energy recovery

• Main Authors: Chengwei Sun, Liang Chu, Jianhua Guo, Dapai Shi, Tianjiao Li, Yunsong Jiang
• Format: Article
• Language: English
• Published: SAGE Publishing 2017-11-01
• Series: Advances in Mechanical Engineering
• Online Access: https://doi.org/10.1177/1687814017734994

In this article, an adaptive cruise control algorithm with braking energy recovery is proposed. First, the influence of the working characteristics of motor and battery on the energy recovery is analyzed in the braking energy recovery system. Considering the requirements of the braking regulations, the genetic algorithm is used to optimize the economy and safety during the braking energy recovery process. Braking force allocation strategy results can be obtained by offline lookup table. Based on the model predictive control theory with particle swarm optimization algorithm, an adaptive cruise control strategy is constructed to recover the braking energy as much as possible under the premise of satisfying vehicle tracking, safety, and comfort performance. Use Carsim as the simulation platform, and then co-simulate it with MATLAB/Simulink which is embedded with control algorithm. Simulation results show that distance error ratio and speed error ratio are mostly within 10%, braking energy recovery rate can up to 43.65% or more.The stability and comfort performance can also meet the control requirement.