Research on Regenerative Braking Control Strategy for Single-Pedal Pure Electric Commercial Vehicles

Abstract

In recent years, with the increasing severity of energy and environmental issues, countries have vigorously developed the new energy automotive industry. To reduce the difficulty of driver operation and increase endurance mileage, this article proposes a regenerative braking control strategy for a single-pedal pure electric commercial vehicle. Firstly, the single-pedal control system’s hierarchical approach was designed to contain the driver’s intention analysis and torque calculation layers. After identifying the driver’s intention, a logic threshold method was used to determine the braking pattern. Then, a fuzzy theory was used, with road gradient, braking strength, and speed as input parameters, and the ratio coefficient of braking force as the output parameter. A hybrid regenerative braking strategy was formulated based on the ideal distribution curve. Finally, the proposed strategy was verified through simulation and a constant-speed car-following experiment. The constant-speed car-following experiment results show that the maximum optimization rate of energy consumption provided by the proposed single-pedal regenerative braking control strategy is 5.81%, and the average optimization rate is 4.33%. This strategy can effectively reduce energy consumption and improve the economic performance of single-pedal pure electric commercial vehicles.

Neural Sliding Mode Control of a Buck-Boost Converter Applied to a Regenerative Braking System for Electric Vehicles

“…The primary goal of implementing regenerative braking systems in EVs is to recover the kinetic energy produced during motor deceleration, resulting in increased energy storage capacity and increased driving distance [3]. In [4], a regenerative braking system with one single braking pedal decreased the energy consumption and improved the commercial cost of EVs.…”

Long Downhill Braking and Energy Recovery of Pure Electric Commercial Vehicles

“…In the study of Wei Zhang et al [7], based on Matlab/Simulink and ADVISOR, the vehicle model is established, and the regenerative braking priority control strategy is adopted to distribute the axle load and braking force on the uphill and downhill road slope to maximize the recovery of braking energy. In the study of Zhe Li et al [8], based on the driver's braking intention, the braking mode is determined by fuzzy theory and logical threshold method, and the braking energy is recovered by fuzzy control rules with road slope, braking intensity and speed as input parameters and braking force proportional coefficient as output parameters. Longlong Wei et al [9] proposed a brake power distribution control strategy for front and rear wheels based on braking intent recognition, which takes the effect of retarder on brake power distribution into account and maximizes the braking energy recovery.…”