scholarly journals Optimal Cooperative Brake Distribution Strategy for IWM Vehicle Accounting for Electric and Friction Braking Torques

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Michele Vignati ◽  
Mattia Belloni ◽  
Davide Tarsitano ◽  
Edoardo Sabbioni
Keyword(s):  
Normal Load ◽  
Stability Control ◽  
Regenerative Braking ◽  
Electric Motors ◽  
Braking Performance ◽  
Motor Efficiency ◽  
Braking Torque ◽  
Stability Control System ◽  
Efficiency Map ◽  
Yaw Moment

Electric vehicles are spreading in automotive industry pushed by the need of reducing greenhouse gas. However, the use of multiple electric motors, i.e., one per wheel, allows to redefine the vehicle powertrain layout with great benefits on vehicle dynamics. Electric motors braking torque is in general not enough to produce high decelerations. Hydraulic friction brakes are still necessary for safety reasons and to avoid oversized motors. This paper presents a control strategy for distributed electric motors (EM), one per wheel, to maximize the regenerative braking. The controller handles cooperative braking among EMs and hydraulic brakes, which are still necessary to guarantee top braking performance of the car. The proposed algorithm considers the driver requested braking torque as well as the required yaw moment by stability control system. Motor efficiency map and wheel normal load are considered to optimally distribute the torques. With respect to conventional distribution strategies, the presented algorithm improves performance, maximizing the regenerative braking power.

Vehicle Direct Yaw Moment Control with Longitudinal Forces Distribution

2014 ◽  
Vol 709 ◽  
pp. 331-334
Author(s):  
Man Hong Huang ◽  
Huan Shen ◽  
Yun Sheng Tan
Keyword(s):  
Control System ◽  
Reference Model ◽  
Sliding Mode ◽  
Stability Control ◽  
Yaw Rate ◽  
Vehicle Stability Control ◽  
Braking Torque ◽  
Stability Control System ◽  
Yaw Moment Control ◽  
Yaw Moment

In this paper, a vehicle stability control system is proposed to improve vehicle comfort, handling and stability. The control system includes reference model, DYC controller and Distributer. Reference model is used to obtain the desired yaw rate. DYC controller determines the desired yaw moment by means of sliding-mode technique. Distributer, based on maneuverability and comfort, distributes driving torque or braking torque according to the desired yaw rate. Simulation result shows that the proposed control algorithm can improve vehicle handling and stability effectively.

scholarly journals Energy saving control based on motor efficiency map for electric vehicleswith four-wheel independently driven in-wheel motors

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879306 ◽  
Author(s):  
Li Gang ◽  
Yang Zhi
Keyword(s):  
Energy Saving ◽  
Electric Vehicles ◽  
Control Method ◽  
Regenerative Braking ◽  
Motor Efficiency ◽  
Wheel Drive ◽  
Braking Torque ◽  
Braking Control ◽  
Efficiency Map ◽  
Energy Saving Control

For four-wheel independently driven in-wheel motor electric vehicles, the four-wheel drive/braking torque can be controlled independently. Therefore, it has an advantage that energy saving control can be applied effectively. This article studies several energy saving control methods from two levels of driving and braking for four-wheel independently driven in-wheel motor electric vehicles under urban conditions based on the motor efficiency map. First, the energy saving control logic and the evaluation index were proposed in the article. The four-wheel drive torque was online optimized in real time through drive energy saving control, in order to improve the driving efficiency in the driving process of electric vehicles. According to the theory of ideal braking force distribution and Economic Commission of Europe braking regulations, the parallel regenerative braking control method based on the motor efficiency map was then studied. The parallel regenerative braking control method was applied to four-wheel independently driven in-wheel motor electric vehicles. The simulation analysis under typical urban driving cycle conditions was carried out to determine the braking intensity of the parallel brake front axle separate regenerative braking, and finally the braking energy recovery rate of electric vehicle can be improved in the low speed and low braking torque. Finally, simulation experiments have been carried out to verify the researched method under the NEDC, UDDS, and J1015 urban driving cycles. The simulation results show that the energy saving control methods have an obvious effect on energy saving under the urban driving cycle conditions.

scholarly journals Hierarchical Coordinated Control Method of In-Wheel Motor Drive Electric Vehicle Based on Energy Optimization

2019 ◽  
Vol 10 (2) ◽  
pp. 15 ◽  
Author(s):  
Junchang Wang ◽  
Junmin Li
Keyword(s):  
Electric Vehicle ◽  
Control Method ◽  
Energy Optimization ◽  
Coordinated Control ◽  
Stability Control ◽  
Motor Drive ◽  
Motor Efficiency ◽  
Bicycle Model ◽  
Optimization Control ◽  
Efficiency Map

In order to improve the endurance mileage and stability of an electric vehicle at the same time, a hierarchical coordinated control method of an in-wheel motor drive electric vehicle based on energy optimization is presented in this paper. The driving architecture of an in-wheel motor drive electric vehicle is developed, and a corresponding simulation model is established in CarSim software; then, the bicycle model of an electric vehicle is derived from vehicle dynamic equations. The energy-saving feasibility of an in-wheel motor drive electric vehicle is analyzed by a motor efficiency map, and on the basis of this, the hierarchical coordinated control method is proposed to achieve the simultaneous energy optimization control and stability control of the electric vehicle. The results show that the energy consumption is decreased by 32.41%, 45.92%, and 4.07% in different simulation manoeuver cases, and the vehicle stability can be ensured by the proposed control method.

Vehicle handling and stability control by the cooperative control of 4WS and DYC

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740090 ◽  
Author(s):  
Huan Shen ◽  
Yun-Sheng Tan
Keyword(s):  
Control System ◽  
Cooperative Control ◽  
Sliding Mode ◽  
Integrated Control ◽  
Longitudinal Velocity ◽  
Stability Control ◽  
Sideslip Angle ◽  
Vehicle Handling ◽  
Braking Torque ◽  
Yaw Moment

This paper proposes an integrated control system that cooperates with the four-wheel steering (4WS) and direct yaw moment control (DYC) to improve the vehicle handling and stability. The design works of the four-wheel steering and DYC control are based on sliding mode control. The integration control system produces the suitable 4WS angle and corrective yaw moment so that the vehicle tracks the desired yaw rate and sideslip angle. Considering the change of the vehicle longitudinal velocity that means the comfort of driving conditions, both the driving torque and braking torque are used to generate the corrective yaw moment. Simulation results show the effectiveness of the proposed control algorithm.

Stability Control of 4WD Electric Vehicle with In-Wheel Motors Based on Integrated Control of Electro-Mechanical Braking System

2015 ◽  
Vol 740 ◽  
pp. 206-210
Author(s):  
Chuan Xue Song ◽  
Feng Xiao ◽  
Shi Xin Song ◽  
Si Lun Peng ◽  
Shi Qi Fan
Keyword(s):  
Electric Vehicle ◽  
Fuzzy Controller ◽  
Mechanical Load ◽  
Integrated Control ◽  
Stability Control ◽  
Vehicle Stability ◽  
Vehicle Stability Control ◽  
Potential Applications ◽  
Stability Control System ◽  
Yaw Moment

Each wheel torque can be controlled independently, so four-wheel-drive electric vehicle can not only control the vehicle stability through hydraulic braking pressure regulation, but also through controlling the motor driving and braking force to generate yaw moment, which are different with the conventional vehicles. 4WD Evs have potential applications in control engineering. Both in-wheel motors and the EHB are actuators for vehicle stability control. In this paper, a vehicle co-simulation platform is constructed through the application of AMEsim and Simulink, additionally, a fuzzy controller is designed to generate yaw moment so as to compensate for deviations between CG slip angles and yaw rate. The simulation results show that the stability control system with motors and a mechanical load brake system can effectively improve the handling stability of the vehicle.

Design and Simulation of a Stability Control System for 4 Independent Wheel Drive Electric Vehicle

2016 ◽  
Author(s):  
Juan S. Núñez ◽  
Luis E. Muñoz
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Sliding Mode ◽  
Stability Control ◽  
Performance Comparison ◽  
Phase Portraits ◽  
Vehicle Model ◽  
Stability Control System ◽  
The Stability ◽  
Yaw Moment

With the aim of prevent situations of vehicle instability against different driving maneuvers, the vehicle yaw stability becomes crucial for safe operation. This paper presents the design and simulation of a traction and a stability control system algorithms for independent four-wheel-driven electric vehicle. The stability control system consists of a multilevel algorithm divided into a high level controller and a low level controller. First, an analysis of the stability of the vehicle is performed using phase portraits analysis, both in open loop and closed loop. The stability control system is designed to generate a desired yaw moment according to the steady state cornering relationship with the steering angle input. As the test vehicle, a 14 DoF vehicle model is proposed including nonlinear tire models that allow the generation of combined forces. The vehicle model includes the powertrain dynamics. The yaw moment generation is performed using the traction and braking forces between the tires of each side of both front and rear axle. In order to generate the maximum traction forces in each of the wheels, a traction and a braking control is developed via a sliding mode controller scheme. Finally a performance comparison between a controlled and an uncontrolled vehicle is presented. The behavior of both vehicles is simulated using a classical double lane change driving maneuver.

Simulating Research of Integrated Control for Automobile Steering Stability

2011 ◽  
Vol 130-134 ◽  
pp. 2190-2193
Author(s):  
Chuan Long Shi ◽  
Chuan Hui Liu
Keyword(s):  
Integrated Control ◽  
Nonlinear Effects ◽  
Stability Control ◽  
Lateral Acceleration ◽  
Slip Angle ◽  
Software Environment ◽  
Stability Performance ◽  
Stability Control System ◽  
Integrated Controller ◽  
Yaw Moment

In this paper, four-wheel steering and direct yaw-moment integrated controller is designed. To verify the effectiveness of the integrated controller, a nonlinear three-degree-of-freedom model is employed for computer simulation. Considering the nonlinear effects of tyre, Pacejka tyre model was adopted to set up the nonlinear vehicle dynamic model. The direct yaw-moment controller was designed based on optimal control theory. Simulation on the nonlinear vehicle with integrated controller in Matlab/Simulink software environment was described. The simulations suggest, compared with FWS and 4WS, the integrated controller can make the handling and stability performance on big lateral acceleration and slip angle improved, and make the driver drive the vehicle normally. The conclusion can be useful for the system design of vehicle stability control system.

A hybrid stability-control system: combining direct-yaw-moment control and G-Vectoring Control

2012 ◽  
Vol 50 (6) ◽  
pp. 847-859 ◽  
Author(s):  
Junya Takahashi ◽  
Makoto Yamakado ◽  
Shinjiro Saito ◽  
Atsushi Yokoyama
Keyword(s):  
Control System ◽  
Stability Control ◽  
Direct Yaw Moment Control ◽  
Stability Control System ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Yaw Moment

Development of Trunk Transmission Online Integrated Stability Control System (ISC) for New Generation Grid

2017 ◽  
Vol 137 (6) ◽  
pp. 434-445 ◽  
Author(s):  
Hiroshi Yoshida ◽  
Ryuji Tachi ◽  
Koya Takafuji ◽  
Hironori Imaeda ◽  
Masaru Takeishi ◽  
...  
Keyword(s):  
Control System ◽  
Stability Control ◽  
Stability Control System ◽  
New Generation
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