scholarly journals Research on Control Strategy of Hydraulic Regenerative Braking of Electrohydraulic Hybrid Electric Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghai Zhao ◽  
Hongxin Zhang ◽  
Yafei Xin
Keyword(s):  
Electric Vehicle ◽  
Electric Drive ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Drive System ◽  
Regenerative Braking ◽  
Electric Drive System ◽  
Hybrid Electric ◽  
The Impact

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.

scholarly journals Cooperative Control of Regenerative Braking and Antilock Braking for a Hybrid Electric Vehicle

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Guodong Yin ◽  
XianJian Jin
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Regenerative Braking ◽  
Braking System ◽  
Antilock Braking System ◽  
Braking Torque ◽  
Antilock Braking ◽  
Hybrid Electric ◽  
Braking Control

A new cooperative braking control strategy (CBCS) is proposed for a parallel hybrid electric vehicle (HEV) with both a regenerative braking system and an antilock braking system (ABS) to achieve improved braking performance and energy regeneration. The braking system of the vehicle is based on a new method of HEV braking torque distribution that makes the antilock braking system work together with the regenerative braking system harmoniously. In the cooperative braking control strategy, a sliding mode controller (SMC) for ABS is designed to maintain the wheel slip within an optimal range by adjusting the hydraulic braking torque continuously; to reduce the chattering in SMC, a boundary-layer method with moderate tuning of a saturation function is also investigated; based on the wheel slip ratio, battery state of charge (SOC), and the motor speed, a fuzzy logic control strategy (FLC) is applied to adjust the regenerative braking torque dynamically. In order to evaluate the performance of the cooperative braking control strategy, the braking system model of a hybrid electric vehicle is built in MATLAB/SIMULINK. It is found from the simulation that the cooperative braking control strategy suggested in this paper provides satisfactory braking performance, passenger comfort, and high regenerative efficiency.

scholarly journals Energy Management Strategy Design and Simulation Validation of Hybrid Electric Vehicle Driving in an Intelligent Fleet

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1516
Author(s):  
Xin Ye ◽  
Fei Lai ◽  
Zhiwei Huo
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Combination Method ◽  
Driving Safety ◽  
System Efficiency ◽  
Hybrid Electric ◽  
The Impact

This paper proposes a combination method of longitudinal control and fuel management for an intelligent Hybrid Electric Vehicle (HEV) fleet. This method can reduce the fuel consumption while maintaining the distance and speed for each vehicle in the fleet. An HEV system efficiency model was established to simulate the impact of different working modes. Based on the principle of optimal vehicle system efficiency, the energy management control strategy of HEV was designed. Then, the driver model of the piloting vehicle and the following vehicle was built by using an intelligent fuzzy control method. Finally, the intelligent fleet model and energy matching model of HEV were integrated with the simulation platform that was developed based on MATLAB/Simulink/Stateflow. The validity of the energy matching strategy of HEV under the principle of optimal system efficiency was verified by simulation results, and the purpose of improving the driving safety, traffic efficiency, and fuel economy of the fleet was achieved. Comparing with the conventional control strategy, the proposed method saved 7.79% of fuel for the HEV fleet. Meanwhile, the distance ranges between the vehicles were from 12 meters to 15 meters, which improved the driving safety, passing rate, and fuel economy.

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