An Innovative Design of Decoupled Regenerative Braking System for Electric City Bus Based on Chinese Typical Urban Driving Cycle

Abstract

This paper proposes a novel decoupled approach of a regenerative braking system for an electric city bus, aiming at improving the utilization of the kinetic energy for rear axle during a braking process. Three contributions are added to distinguish from the previous research. Firstly, an energy-flow model of the electric bus is established to identify the characteristic parameters which affect the energy-saving efficiency of the vehicle, while the key parameters (e.g., driving cycles and the recovery rate of braking energy) are also analyzed. Secondly, a decoupled braking energy recovery scheme together with the control strategy is developed based on the characteristics of the power assistance for electric city bus which equips an air braking system, as well as the regulatory requirements of ECE R13. At last, the energy consumption of the electric city bus is analyzed by both the simulation and vehicle tests, when the superimposed and the decoupled regenerative braking system are, respectively, employed for the vehicle. The simulation and actual road test results show that compared with the superposition braking system of the basic vehicle, the decoupled braking energy recovery system after the reform can improve the braking energy recovery rate and vehicle energy-saving degree. The decoupled energy recovery system scheme and control strategy proposed in this paper can be adopted by bus factories to reduce the energy consumption of pure-electric buses.

Design Optimization of Underground Mining Vehicles Based on Regenerative Braking Energy Recovery

“…Currently, regenerative braking systems are classified into two types based on the decoupling of the brake pedal force and hydraulic braking force: additive regenerative braking system (RBS) and cooperative regenerative braking system (CRBS). To determine the most efficient and concise system for energy recovery, a comparison between these two regenerative braking systems is conducted [16].…”

Artificial Neural Networks: A Promising Tool for Regenerative Braking Control in Electric Vehicles

“…It was mentioned that, integrating RBS in buses and trains can reduce fuel consumption by about 30% and increase energy efficiency to 30% [4], [8], [10], [11]. To ensure the efficiency of the energy recovery process some parameters must be considered such as the type of used motor, the applied braking force and EV batteries, different road surfaces coefficients, driver intentions, state of charge of the battery, drive distance, motor braking torque and braking forces distribution on the wheels [2], [9], [12].…”