scholarly journals Estimation of Longitudinal Force and Sideslip Angle for Intelligent Four-Wheel Independent Drive Electric Vehicles by Observer Iteration and Information Fusion

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1268 ◽  
Author(s):  
Te Chen ◽  
Long Chen ◽  
Xing Xu ◽  
Yingfeng Cai ◽  
Haobin Jiang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Information Fusion ◽  
Longitudinal Force ◽  
Sideslip Angle

scholarly journals Stability Control for Electric Vehicles with Four In-Wheel-Motors Based on Sideslip Angle

2021 ◽  
Vol 12 (1) ◽  
pp. 42
Author(s):  
Kun Yang ◽  
Danxiu Dong ◽  
Chao Ma ◽  
Zhaoxian Tian ◽  
Yile Chang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Control Method ◽  
Sliding Mode ◽  
Stability Control ◽  
Torque Control ◽  
Wheel Load ◽  
Sideslip Angle ◽  
Distribution Method ◽  
Load Rate ◽  
The Stability

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors.

Information Fusion for State Estimation of Power Battery in Electric Vehicle Based on Unscented Kalman Filter

2013 ◽  
Vol 303-306 ◽  
pp. 975-978
Author(s):  
Hong Yu Zheng ◽  
Chang Fu Zong
Keyword(s):  
Kalman Filter ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Information Fusion ◽  
Unscented Kalman Filter ◽  
Accurate Estimate ◽  
Fusion Algorithm ◽  
Power Battery ◽  
Battery State Of Charge ◽  
New Generation

The power battery state of charge (SOC) in electric vehicles is not easy to measure accurately or apply a sensor but the expense is increased. However the variable of SOC is great importance to control of electric vehicles. A power battery model is built by the Partnership for a New Generation of Vehicles (PNGV) model to estimate the state of SOC. In order to make a high accurate estimate for SOC value, an information fusion algorithm based on unscented kalman filter (UKF) is introduced to design an observer. The test results show that the observer based information fusion and UKF are effective and accuracy, so it is may apply it the electric vehicle control and observation.

scholarly journals A Robust Control Method for Lateral Stability Control of In-Wheel Motored Electric Vehicle Based on Sideslip Angle Observer

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yaxiong Wang ◽  
Feng Kang ◽  
Taipeng Wang ◽  
Hongbin Ren
Keyword(s):  
Robust Control ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Control Method ◽  
Stability Control ◽  
Lateral Stability ◽  
Level Control ◽  
Sideslip Angle ◽  
Safety Control ◽  
Yaw Moment

In-wheel motored powertrain on electric vehicles has more potential in maneuverability and active safety control. This paper investigates the longitudinal and lateral integrated control through the active front steering and yaw moment control systems considering the saturation characteristics of tire forces. To obtain the vehicle sideslip angle of mass center, the virtual lateral tire force sensors are designed based on the unscented Kalman filtering (UKF). And the sideslip angle is estimated by using the dynamics-based approaches. Moreover, based on the estimated vehicle state information, an upper level control system by using robust control theory is proposed to specify a desired yaw moment and correction front steering angle to work on the electric vehicles. The robustness of proposed algorithm is also analyzed. The wheel torques are distributed optimally by the wheel torque distribution control algorithm. Numerical simulation is carried out in Matlab/Simulink-Carsim cosimulation environment to demonstrate the effectiveness of the designed robust control algorithm for lateral stability control of in-wheel motored vehicle.

Analysis of the Lateral Stability for Four-Wheel Independent Driving Electric Vehicles

2014 ◽  
Vol 590 ◽  
pp. 394-398 ◽  
Author(s):  
Liang Zheng ◽  
Jun Ye
Keyword(s):  
Electric Vehicles ◽  
Hot Spot ◽  
Lateral Stability ◽  
Sideslip Angle ◽  
Yaw Rate ◽  
Excellent Control ◽  
Control Capability ◽  
And Performance ◽  
Drive Systems ◽  
Major Factors

The four-wheel independent driving EVs have been considered as the hot spot due to their excellent controlling capability of the driving force distribution in recent years. In order to achieve the excellent control capability of electric drive systems, the mechanical properties and performance need to be investigated and evaluated. In this paper, the lateral stability of four-wheel independent driving EVs is studied and the major factors are investigated. Results of the analysis indicate that the sideslip angle of the vehicle should be controlled at a small value. Under this condition, the yaw rate plays a key role on the lateral stability of the vehicle. The results in this research provide a solid guidance to considerably improve the lateral stability and the active safety of the EVs, in both theoretical and practical aspects.

scholarly journals An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

Meccanica ◽  
2021 ◽  
Author(s):  
Andrea Mangia ◽  
Basilio Lenzo ◽  
Edoardo Sabbioni
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicles ◽  
Degrees Of Freedom ◽  
Integrated Approach ◽  
Sideslip Angle ◽  
Control Framework ◽  
Torque Vectoring ◽  
Wheel Torque ◽  
High Level ◽  
Yaw Moment

AbstractA key feature achievable by electric vehicles with multiple motors is torque-vectoring. Many control techniques have been developed to harness torque-vectoring in order to improve vehicle safety and energy efficiency. The majority of the existing contributions only deal with specific aspects of torque-vectoring. This paper presents an integrated approach allowing a smooth coordination among the main blocks that constitute a torque-vectoring control framework: (1) a reference generator, that defines target yaw rate and sideslip angle; (2) a high level controller, that works out the required total torque and yaw moment at the vehicle level; (3) a low level controller, that maps the required force and yaw moment into individual wheel torque demands. In this framework, the driver can select one among a number of driving modes that allow to change the vehicle cornering response and, as a second priority, maximise energy efficiency. For the first time, the selectable driving modes include an “Energy efficiency” mode that uses torque-vectoring to prioritise the maximisation of the vehicle energy efficiency, thus further increasing the vehicle driving range. Simulation results show the effectiveness of the proposed framework on an experimentally validated 14 degrees of freedom vehicle model.

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