Study on the Stability Control Strategy of Central-China Power Grid During Asynchronous Operation Test of Hubei and Chongqing

2021 ◽  
Author(s):  
Haiguang Liu ◽  
Kan Cao ◽  
Ying Wang ◽  
Chu Zhou ◽  
Min Xu
Keyword(s):  
Control Strategy ◽  
Power Grid ◽  
Stability Control ◽  
Central China ◽  
Asynchronous Operation ◽  
Operation Test ◽  
The Stability

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 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

Response control of a floating airport in heading waves with output saturation

2018 ◽  
Vol 25 (3) ◽  
pp. 571-580
Author(s):  
Shuyan Xia ◽  
Daolin Xu ◽  
Haicheng Zhang ◽  
Yousheng Wu
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Stability Control ◽  
Control Law ◽  
Backstepping Method ◽  
Floating Platform ◽  
Nonlinear Dynamic Model ◽  
Floating Structure ◽  
The Stability ◽  
Floating Airport

This paper presents a nonlinear control strategy to stabilize the response of a floating platform in waves. The floating platform consists of multiple floating modules connected in sequence with flexible connectors. A nonlinear dynamic model with a number of controllers is developed for the stability control of the chain-shape floating structure. The backstepping method in conjunction with the Lyapunov stability criteria is proposed to derive the control law for each of the control actuators where the actuator forces are limited with output saturation. The numerical experiments illustrate the feasibility and effectiveness of the control strategy in various conditions of heading waves. The performance of the control method is discussed, especially associated with the saturated output.

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.

Shared Control Strategy for Vehicle Stability on U-Split Road

2019 ◽  
Author(s):  
Liangyao Yu ◽  
Lanie Abi ◽  
Zhenghong Lu ◽  
Yaqi Dai
Keyword(s):  
Control Strategy ◽  
Response Speed ◽  
Steering System ◽  
Stability Control ◽  
Front Wheel ◽  
Shared Control ◽  
Steering Wheel ◽  
Vehicle Dynamic ◽  
Stability Performance ◽  
The Stability

Abstract The steer-by-wire (SBW) system eliminates the mechanical connection between the steering wheel and the carriage wheel. It eliminates various limitations of the traditional steering system, so that the steering ratio of the car can be freely designed and the steering by wire system can achieve good active front wheel steering (AFS) function. In the study of the stability control of vehicles on the μ-split road, there are mainly two methods, one based on vehicle trajectory maintenance and the other based on vehicle dynamic stability control. Both of these control methods have delays, which is not conducive to the trajectory flowing ability of the vehicle when driving on the μ-split road. A shared control strategy is proposed to improve the vehicle’s stability. The purpose of this study is to establish different variable transmission ratio characteristic curves according to the different input signals of the driver and the vehicle, such as angular change speed, steering wheel angle, etc. Based on these conditions, a new model combining driver’s intention with vehicle dynamic model is established, so as to achieve the purpose of judging the stability of vehicle in advance, to reduce the delay time of control and to improve the response speed, which will improve the stability performance of the vehicle.

Stability control of in-wheel motor electric vehicles under extreme conditions

2018 ◽  
Vol 41 (10) ◽  
pp. 2838-2850 ◽  
Author(s):  
Zijun Zhang ◽  
Wanzhong Zhao ◽  
Chunyan Wang ◽  
Liang Li
Keyword(s):  
Electric Vehicles ◽  
Control Strategy ◽  
Lower Layer ◽  
Stability Control ◽  
Extreme Conditions ◽  
Initial Values ◽  
Yaw Moment Control ◽  
Nonlinear Vehicle Model ◽  
The Stability ◽  
Three Degree Of Freedom

To investigate the stability of in-wheel motor electric vehicles (IWMEVs) under extreme conditions, a novel control strategy including active rear steering (ARS) mode and direct yaw moment control (DYC) mode is proposed in this paper, utilizing the adaptive dynamic neural network (ADNN) algorithm to make the most of the two control modes. Firstly, a three-degree of freedom nonlinear vehicle model as well as some subsystems is established. Then, a two-layer stability control strategy is put forward, where the upper-layer calculates the desired rear steering angle as well as the differential torque of the rear wheels and the lower-layer executes commands and returns relevant signals. Besides, a stability controller based on ADNN algorithm is designed in the upper-layer so as to take advantage of the two modes under extreme conditions. Next, the impacts of initial values of the connection weights on the ability of ADNN algorithm to train and learn are revealed. Consequently, the optimal initial values can be ascertained before the following simulations. Finally, the closed loop simulations of ARS and DYC are carried out under some extreme conditions such as high velocity and low adhesion coefficient roads, and the results indicate that compared with DYC’s difficulty in playing its role, ARS mode can significantly improve the stability of IWMEVs even under extreme conditions.

scholarly journals Stability Control of Vehicle Emergency Braking with Tire Blowout

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Qingzhang Chen ◽  
Youhua Liu ◽  
Xuezhi Li
Keyword(s):  
Intellectual Property ◽  
Control Strategy ◽  
Test System ◽  
Stability Control ◽  
Emergency Braking ◽  
Slowing Down ◽  
Braking System ◽  
Motion State ◽  
The Stability

For the stability control and slowing down the vehicle to a safe speed after tire failure, an emergency automatic braking system with independent intellectual property is developed. After the system has received a signal of tire blowout, the automatic braking mode of the vehicle is determined according to the position of the failure tire and the motion state of vehicle, and a control strategy for resisting tire blowout additional yaw torque and deceleration is designed to slow down vehicle to a safe speed in an expected trajectory. The simulating test system is also designed, and the testing results show that the vehicle can be quickly stabilized and kept in the original track after tire blowout with the emergency braking system described in the paper.

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