Velocity Optimization for Braking Energy Management of In-Wheel Motor Electric Vehicles

Abstract

This paper presents two braking regenerative energy optimization controllers for in-wheel motor electric vehicles. The first one is a velocity-tracking controller based on a model predictive control (MPC) method to recover the braking energy. It takes the front and rears in-wheel motor efficiencies into account to distribute the hydraulic and in-wheel motor braking torque of the front and rear wheels. As the vehicle information and intelligence have brought new opportunities for energy management, another velocity optimization controller is designed by considering the restricted condition of terminal distance and terminal velocity. In this strategy, a receding-horizon MPC method is proposed to solve the restricted nonlinear optimal problem. Furthermore, this optimization algorithm is transformed from the time horizon to the distance horizon to satisfy the terminal distance constraint. AMESim/Simulink co-simulations are carried out to evaluate the effectiveness of the proposed controllers. The simulation results indicate that the velocity optimization method can achieve the braking requirement as well as effectively promote regenerative efficiency. INDEX TERMS Electric vehicle, regenerative braking, energy management, model predict control.

A review on braking control and optimization techniques for electric vehicle

“…This system is tested with the ''NEDC'' cycle and contributes 5.1% more efficiency than rule-based control method. 14 Reduction in braking time is achieved by 11.4% by controlling RBS with a sliding mode controller with maintaining wheel slip and tire-road friction within stability limits. The proposed methodology shown in Figure 5 enhances vehicle stability by preventing skidding during braking operation.…”

Energy Recovery Strategy Based on Ideal Braking Force Distribution for Regenerative Braking System of a Four-Wheel Drive Electric Vehicle

“…Due to the continuous depletion of global nonrenewable fossil fuels, the energy crisis is becoming more prominent than ever [1]. To mitigate the energy crisis, researchers have been making a lot of efforts in the fields of renewable energy [2][3][4], energy recovery [5][6][7][8], energy storage [9,10], energy efficiency [11][12][13][14] et al In automobile industry, electric vehicles (EVs) have been an alternative solution owing to its high energy efficiency, low noise, and zero emission [15]. However, the short driving range is an urgent problem to be solved.…”

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

“…Sun et al [11] integrated the braking control strategy to met with the requirement of high braking stability and energy regeneration rate, which including three braking force operating modes. Xu et.al [12] presented two braking regenerative energy optimization controllers to promote regenerative energy, it considering motor efficiency to distribute the friction and motor braking torque of the front and rear wheels. Li et al [13] proposed a composite RBS to optimize regenerative and plugging 1 School of Mechanical Engineering, Southeast University, Nanjing 211189, China braking simultaneously with the driver's intention recognition.…”

“…Lian et al [14] designed an optimal braking force distribution strategy, while uses a safety distance model to avoid collision. In addition, the rule-based algorithm [9], PID algorithm [15], sliding mode control [16], fuzzy logic control [17], design of experiment method [11], model predictive control (MPC) [12], and dynamic programming (DP) [18] were adopted to refine the RBS.…”