Effective Brake Torque Allocation in Regenerative Braking System Considering Shaft Vibration Using Model Predictive Control

Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems ◽

10.1115/dscc2015-9996 ◽

2015 ◽

Author(s):

Bhushan Naik ◽

Taehyun Shim

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Electric Vehicles ◽

Control Method ◽

Brake Torque ◽

Stopping Distance ◽

Quarter Car Model ◽

Braking System ◽

Car Model ◽

Electric Drive System

A regenerative brake system is an effective way of recovering energy that would be lost as heat during brake operation, and such systems are widely used in hybrid and electric vehicles. This paper presents a multi-objective method for allocating brake torque between the hydraulic and regenerative brake systems using model predictive control. The proposed control method has two objectives: bandwidth-based torque allocation and reduction in driveshaft vibrations. A quarter-car model with a PMSM electric drive system is used to investigate this control method’s effectiveness. The simulation results show that the vehicle stopping distance and the drive shaft vibrations will be reduced with the proposed control strategy.

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Model Predictive Control for Connected Hybrid Electric Vehicles

Mathematical Problems in Engineering ◽

10.1155/2015/318025 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Kaijiang Yu ◽

Xiaozhuo Xu ◽

Qing Liang ◽

Zhiguo Hu ◽

Junqi Yang ◽

...

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Electric Vehicles ◽

Fuel Economy ◽

Hybrid Electric Vehicle ◽

Hybrid Electric Vehicles ◽

Control Method ◽

Fuel Efficiency ◽

Computation Method ◽

Hybrid Electric

This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV forPbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

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Adaptive Model Predictive Control Research on Regenerative Braking for Electric Bus Cruising Downhill

Journal of Advanced Manufacturing Systems ◽

10.1142/s0219686716500104 ◽

2016 ◽

Vol 15 (03) ◽

pp. 133-150 ◽

Cited By ~ 1

Author(s):

Zhao Guo-Zhu ◽

Huang Xiang ◽

Peng Xing

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Control Method ◽

Least Square ◽

Mode Switching ◽

Regenerative Braking ◽

Adaptive Model ◽

Recursive Least Square ◽

Braking System ◽

Adaptive Model Predictive Control

To use regenerative brake and mechanical brake co-operatively to maintain the constant speed and the braking energy can be regenerated as much as possible when vehicles travel downhill, the mathematical model of the braking system is established, and the adaptive model predictive control method is adopted to control the speed of vehicles. The recursive least square algorithm with the forgetting factor is used to identify the road gradient online. And then the control results of the adaptive model predictive control are compared with the results of PID control, simulation results show that the robustness and the stability of the adaptive model predictive control method are better. The speed can be maintained basic stability with the coordinated use of the regenerative braking and the mechanical braking. Meanwhile, the braking energy can be regenerated as much as possible as the regenerative braking system can be used as much as possible. Moreover, as the charge acceptance ability of the battery is restricted, the brake mode switching model is designed. The braking mode can be switched between the electro-mechanical braking system and mechanical braking system according to the SOC of the batteries.

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