Comparison of Control Allocation Algorithms Used in Stability Control of Four In-Wheel-Motors Drive Electric Vehicle

2013 ◽  
Vol 437 ◽  
pp. 669-673 ◽  
Author(s):  
Peng Fei Yang ◽  
Lu Xiong ◽  
Zhuo Ping Yu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Control Strategies ◽  
Optimization Method ◽  
Stability Control ◽  
The Other ◽  
Control Allocation ◽  
The Stability ◽  
Allocation Algorithms ◽  
Real Vehicle

Design the stability control strategy of four in-wheel-motors drive electric vehicle (EV) based on control allocation. Two kinds of control allocation methods are designed in this paper, one is the quadratic programming (QP), and the other is a simplified optimization method (SOM). Comparing and evaluating the control strategies through the co-simulation with MATLAB software and CARSIM software. The results of the simulation show: both strategies could stabilize the vehicle posture well under critical condition. QP has more accuracy than SOM, and could rebuild the system automatically when the motor fails. But the SOM doesn’t need iteration, could be possible to use in the real vehicle.

scholarly journals Vehicle Stability Control Strategy Based on Recognition of Driver Turning Intention for Dual-Motor Drive Electric Vehicle

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Shu Wang ◽  
Xuan Zhao ◽  
Qiang Yu
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control ◽  
Motor Drive ◽  
Vehicle Stability ◽  
Lane Change ◽  
Vehicle Stability Control ◽  
Stability Control System ◽  
The Stability

Vehicle stability control should accurately interpret the driving intention and ensure that the actual state of the vehicle is as consistent as possible with the desired state. This paper proposes a vehicle stability control strategy, which is based on recognition of the driver’s turning intention, for a dual-motor drive electric vehicle. A hybrid model consisting of Gaussian mixture hidden Markov (GHMM) and Generalized Growing and Pruning RBF (GGAP-RBF) neural network is constructed to recognize the driver turning intention in real time. The turning urgency coefficient, which is computed on the basis of the recognition results, is used to establish a modified reference model for vehicle stability control. Then, the upper controller of the vehicle stability control system is constructed using the linear model predictive control theory. The minimum of the quadratic sum of the working load rate of the vehicle tire is taken as the optimization objective. The tire-road adhesion condition, performance of the motor and braking system, and state of the motor are taken as constraints. In addition, a lower controller is established for the vehicle stability control system, with the task of optimizing the allocation of additional yaw moment. Finally, vehicle tests were carried out by conducting double-lane change and single-lane change experiments on a platform for dual-motor drive electric vehicles by using the virtual controller of the A&D5435 hardware. The results show that the stability control system functions appropriately using this control strategy and effectively improves the stability of the vehicle.

scholarly journals Research on the Stability Control Strategy of Four-Wheel Independent Driving Electric Vehicle

Engineering ◽  
2017 ◽  
Vol 09 (03) ◽  
pp. 338-350
Author(s):  
Bo Peng ◽  
Huanhuan Zhang ◽  
Peiteng Zhao
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control ◽  
The Stability

scholarly journals New DTC strategy of multi-machines single-inverter systems for electric vehicle traction applications

2020 ◽  
Vol 11 (2) ◽  
pp. 641
Author(s):  
Taibi Ahmed ◽  
Hartani Kada ◽  
Allali Ahmed
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Control Structure ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Structure Control ◽  
The Subject ◽  
Simulation Results ◽  
The Stability ◽  
Traction System

In high power traction system applications two or more machines are fed by one converter. This topology results in a light, more compact and less costly system. These systems are called multi-machines single-converter systems. The problems posed by different electrical and mechanical couplings in these systems (MMS) affect various stages of the systems and require control strategy to reduce adverse effects. Control of multi-machines single-converter systems is the subject of this paper. The studied MMS is an electric vehicle with four in-wheel PMS motors. A three-leg inverter supplies two permanent magnet synchronous machines which are connected to the front right and rear right wheels, and another inverter supplies the left side. Several methods have been proposed for the control of multi-machines single-inverter systems, the master-slave control structure seems best adapted for our traction system. In this paper, a new control structure based on DTC method is used for the control of bi-machine traction system of an EV. This new control has been implanted in simulation to analyze its robustness in the presence of the various load cases involved in our electric vehicle traction chain. Simulation results indicated that this structure control allowed the stability of the traction system.

Study on the stability control strategy of Triphala solution based on the balance of physical stability and chemical stabilities

2018 ◽  
Vol 158 ◽  
pp. 247-256 ◽  
Author(s):  
Hao-zhou Huang ◽  
Sheng-yu Zhao ◽  
Xiu-mei Ke ◽  
Jun-zhi Lin ◽  
Shu-sen Huang ◽  
...  
Keyword(s):  
Control Strategy ◽  
Physical Stability ◽  
Stability Control ◽  
The Stability

scholarly journals Optimized Handling Stability Control Strategy for a Four In-Wheel Motor Independent-Drive Electric Vehicle

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 17017-17032 ◽  
Author(s):  
Yong Chen ◽  
Sizhong Chen ◽  
Yuzhuang Zhao ◽  
Zepeng Gao ◽  
Changlong Li
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control

Fuzzy Logic Control Strategy for an Extended-Range Electric Vehicle

2012 ◽  
Vol 220-223 ◽  
pp. 968-972 ◽  
Author(s):  
Ji Gao Niu ◽  
Su Zhou
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
High Efficiency ◽  
Control Strategies ◽  
Vehicle Performance ◽  
Logic Control ◽  
Extended Range ◽  
Avl Cruise

This paper presents a Fuzzy Logic Control Strategy (FLCS) for an Extended-range Electric Vehicle (E-REV) with series structure. The control strategy design objective of the E-REV is fuel economy. Based on the State of Charge (SOC) of the battery and the desired power for driving, the power required by the vehicle is split between the engine/generator set and the battery by the FLCS. The engine can be operated consistently in a very high efficiency area and the SOC of the battery can be maintained at a reasonable level. Some standard driving cycles and two control strategies of Power Follower Control Strategy (PFCS) and FLCS were simulated with AVL-Cruise and Matlab/Simulink to analyze the vehicle performance. Some simulation results are compared and discussed: the FLCS indicates better performance in terms of fuel consumption.

Comparison Study on Two Energy Control Strategies of Plug-In Hybrid Electric Vehicle

2011 ◽  
Vol 474-476 ◽  
pp. 1583-1586
Author(s):  
Qing Sheng Shi ◽  
Xiao Ping Zhang ◽  
Lan Wu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Energy Control ◽  
Simulation Experiments ◽  
Engine Efficiency ◽  
Efficiency Control ◽  
Hybrid Electric ◽  
Vehicle Platform

It is of great importance to manage the energy split of plug-in hybrid electric vehicle during the driving process.In this paper, principle of energy control in plug-in hybrid electric vehicle was first presented. And then, two energy control strategies, including fuel control strategy and engine efficiency control strategy, were analyzed, respectively. Finally, comparision simulation experiments were carried on electric vehicle platform ADVISOR software. Simulation results show that, using fuel control strategy can get a better economy performance but worse engine efficiency; while using engine efficiency control strategy can get a better engine efficiency but higher fuel consumption.

scholarly journals Optimal parameters of inverter-based microgrid to improve transient response

2020 ◽  
Vol 10 (1) ◽  
pp. 637
Author(s):  
Sergio Andrés Pizarro Pérez ◽  
John E. Candelo-Becerra ◽  
Fredy E. Hoyos Velasco
Keyword(s):  
Transient Response ◽  
Optimization Algorithm ◽  
Control Strategy ◽  
Control Strategies ◽  
Optimization Method ◽  
Droop Control ◽  
Optimal Parameters ◽  
Power Sources ◽  
Virtual Inertia

The inertia issues in a microgrid can be improved by modifying the inverter control strategies to represent a virtual inertia simulation. This method employs the droop control strategy commonly used to share the power of a load among different power sources in the microgrid. This paper utilizes a modified droop control that represents this virtual inertia and applies an optimization algorithm to determine the optimal parameters and improve transient response. The results show better control when different variations are presented in the loads, leading the microgrid to have a better control of the operation. The optimization method applied in this research allows improvement to the transient response, thus avoiding unnecessary blackouts in the microgrid.

STABILITY CONTROL STRATEGY FOR IN-WHEEL-MOTOR-DRIVE ELECTRIC VEHICLE BASED ON dSPACE

2020 ◽  
Vol 48 (2) ◽  
Author(s):  
Zhang Chuanwei ◽  
Zhang Dongsheng ◽  
Wang Rui ◽  
Zhang Rongbo ◽  
Wen Jianping
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Stability Control ◽  
Motor Drive
Sign in / Sign up

Export Citation Format

Share Document