scholarly journals Torque Coordination Control of an Electro-Hydraulic Composite Brake System During Mode Switching Based on Braking Intention

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2031
Author(s):  
Yang Yang ◽  
Yundong He ◽  
Zhong Yang ◽  
Chunyun Fu ◽  
Zhipeng Cong
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Ride Comfort ◽  
Fuzzy Controller ◽  
Pressure Control ◽  
Smooth Transition ◽  
Mode Switching ◽  
Coordination Control ◽  
Braking System ◽  
Braking Torque

The electro-hydraulic composite braking system of a pure electric vehicle can select different braking modes according to braking conditions. However, the differences in dynamic response characteristics between the motor braking system (MBS) and hydraulic braking system (HBS) cause total braking torque to fluctuate significantly during mode switching, resulting in jerking of the vehicle and affecting ride comfort. In this paper, torque coordination control during mode switching is studied for a four-wheel-drive pure electric vehicle with a dual motor. After the dynamic analysis of braking, a braking force distribution control strategy is developed based on the I-curve, and the boundary conditions of mode switching are determined. A novel combined pressure control algorithm, which contains a PID (proportional-integral-derivative) and fuzzy controller, is used to control the brake pressure of each wheel cylinder, to realize precise control of the hydraulic brake torque. Then, a novel torque coordination control strategy is proposed based on brake pedal stroke and its change rate, to modify the target hydraulic braking torque and reflect the driver’s braking intention. Meanwhile, motor braking torque is used to compensate for the insufficient braking torque caused by HBS, so as to realize a smooth transition between the braking modes. Simulation results show that the proposed coordination control strategy can effectively reduce torque fluctuation and vehicle jerk during mode switching.

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 Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jiankun Peng ◽  
Hongwen He ◽  
Wei Liu ◽  
Hongqiang Guo
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Control Strategies ◽  
Hierarchical Control ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Braking System ◽  
Braking Torque ◽  
Braking Energy Recovery

This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

Optimization of Regenerative Braking Control Strategy for Pure Electric Vehicle

2017 ◽  
Vol 872 ◽  
pp. 331-336 ◽  
Author(s):  
Zhi Jun Guo ◽  
Dong Dong Yue ◽  
Jing Bo Wu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Pso Algorithm ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Constraint Optimization ◽  
Vehicle Model ◽  
Braking Torque ◽  
Braking Control

The regenerative braking strategy for precursor pure electric vehicle was studied in this paper. Firstly, a constraint optimization model was established for the braking force distribution, in which both braking stability and recovery efficiency of braking energy were taken into account. Secondly, Particle Swarm Optimization (PSO) algorithm was applied to optimize the multi key parameters in the model. Finally, the optimized braking torque of the motor was obtained at different speed, different braking strength and different battery charge state. A vehicle model was built to validate the optimized results through simulation. The results showed that, compared with the original control strategy, the optimized control strategy not only could increase the braking stability effectively, but also improve the energy recovery efficiency in a certain extent.

scholarly journals A Novel Torque Coordination Control Strategy of a Single-Shaft Parallel Hybrid Electric Vehicle Based on Model Predictive Control

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Jing Sun ◽  
Guojing Xing ◽  
Xudong Liu ◽  
Xiaoling Fu ◽  
Chenghui Zhang
Keyword(s):  
Electric Vehicle ◽  
Predictive Control ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Coordination Control ◽  
Model Predictive Controller ◽  
Parallel Hybrid Electric Vehicle ◽  
Parallel Hybrid ◽  
Predictive Controller ◽  
Hybrid Electric

The torque coordination control during mode transition is a very important task for hybrid electric vehicle (HEV) with a clutch serving as the key enabling actuator element. Poor coordination will deteriorate the drivability of the driver and lead to excessive wearing to the clutch friction plates. In this paper, a novel torque coordination control strategy for a single-shaft parallel hybrid electric vehicle is presented to coordinate the motor torque, engine torque, and clutch torque so that the seamless mode switching can be achieved. Different to the existing model predictive control (MPC) methods, only one model predictive controller is needed and the clutch torque is taken as an optimized variable rather than a known parameter. Furthermore, the successful idea of model reference control (MRC) is also used for reference to generate the set-point signal required by MPC. The parameter sensitivity is studied for better performance of the proposed model predictive controller. The simulation results validate that the proposed novel torque coordination control strategy has less vehicle jerk, less torque interruption, and smaller clutch frictional losses, compared with the baseline method. In addition, the sensitivity and adaptiveness of the proposed novel torque coordination control strategy are evaluated.

A Research on the Fuzzy Control Strategy for Parallel Hybrid Electric Vehicle

2011 ◽  
Vol 121-126 ◽  
pp. 2522-2526
Author(s):  
Ling Cai ◽  
Liang Ge
Keyword(s):  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Secondary Development ◽  
Simulation Results ◽  
Hybrid Electric ◽  
Fuzzy Control Strategy

Several kinds of methods of energy management of hybrid electric vehicle (HEV) are analyzed. Based on the design requirement of a certain type of parallel HEV, the fuzzy control strategy of energy management is proposed. ADVISOR2002 is chosen as the simulation platform for secondary development, and the simulation results of the fuzzy control strategy and electric assist control strategy are compared. The simulation results indicate that the adaptive fuzzy controller can obviously improve the performance of HEV fuel economy and emissions.

Performance comparison of electric-vehicle drivetrain architectures from a vehicle dynamics perspective

2019 ◽  
Vol 234 (4) ◽  
pp. 915-935
Author(s):  
Kerem Bayar
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Vehicle Dynamics ◽  
Tracking Control ◽  
Tracking Error ◽  
Vehicle Stability ◽  
Electric Motors ◽  
Sideslip Angle ◽  
Stopping Distance ◽  
Braking System

Recent electric vehicle studies in literature utilize electric motors within an anti-lock braking system, traction-control system, and/or vehicle-stability controller scheme. Electric motors are used as hub motors, on-board motors, or axle motors prior to the differential. This has led to the need for comparing these different drivetrain architectures with each other from a vehicle dynamics standpoint. With this background in place, using MATLAB simulations, these three drivetrain architectures are compared with each other in this study. In anti-lock braking system and vehicle-stability controller simulations, different control approaches are utilized to blend the electric motor torque with hydraulic brake torque; motor ABS, torque decomposition, and optimal slip-tracking control strategies. The results for the anti-lock braking system simulations can be summarized as follows: (1) Motor ABS strategy improves the stopping distance compared to the standard anti-lock braking system. (2) In case the motors are not solely capable of providing the required braking torque, torque decomposition strategy becomes a good solution. (3) Optimal slip-tracking control strategy improves the stopping distance remarkably compared to the standard anti-lock braking system, motor anti-lock braking system, and torque decomposition strategies for all architectures. The vehicle-stability controller simulation results can be summarized as follows: (1) higher affective wheel inertia of the on-board and hub motor architecture dictates a higher need of wheel torque in order to generate the tire force required for the desired yaw rate tracking. A higher level of torque causes a higher level of tire slip. (2) Optimal slip-tracking control strategy reduces the tire slip trends drastically and distributes the traction/braking action to each tire with the control-allocation algorithm specifying the reference slip values. This reduces reference tire slip-tracking error and reduces vehicle sideslip angle. (3) Tire slip trends are lower with the hub motor architecture, compared to the other architectures, due to more precise slip control.

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