Network Scheduling for Distributed Controls of Electric Vehicles Considering Actuator Dynamic Characteristics

2017 ◽  
Vol 10 (1) ◽  
pp. 156-164
Author(s):  
Yang Zhao ◽  
Weiwen Deng ◽  
Jian Wu ◽  
Rui He
Keyword(s):  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Network Scheduling ◽  
Distributed Controls

scholarly journals A Control Strategy for Driving Mode Switches of Plug-in Hybrid Electric Vehicles

2018 ◽  
Vol 10 (11) ◽  
pp. 4237 ◽  
Author(s):  
Yuping Zeng ◽  
Zhikai Huang ◽  
Yang Cai ◽  
Yonggang Liu ◽  
Yue Xiao ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Duty Cycle ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Torque Ripple ◽  
Torque Control ◽  
Driving Mode ◽  
Wet Clutch ◽  
Hybrid Electric

Driving mode switches of hybrid vehicles are significant events. Due to the different dynamic characteristics of the engine, motor, and wet clutch, it is difficult to coordinate torque fluctuations caused by mode switches. This paper focused on a control strategy for driving mode switches of plug-in hybrid electric vehicles (PHEVs) with a multi-disk wet clutch. First, the dynamic model of the PHEV was established, and a rule-based control strategy was proposed to divide the working mode regions and distribute the torque between engine and motor. Second, the dual fuzzy control strategy for a wet clutch and the coordinated torque control strategy for driving mode switches were proposed. The dual fuzzy logic control system consisted of the initial pulse-width modulation (PWM)’s duty cycle control and the changing rate of the PWM’s duty cycle control. Considering the difference in the dynamic characteristics between engine, motor, and wet clutch, a coordinated control strategy for the driving mode switches of PHEVs was put forward. Third, simulations of driving mode switches between pure electric driving mode and only engine driving mode were conducted. The results showed that the proposed control strategy could reduce the torque ripple and the jerk of the vehicle, completely satisfying the requirements of China. Finally, the control strategy for the motor-assisted engine starting process was tested on the bench. The experiment results indicated that the proposed control strategy was effective.

scholarly journals Design and Analysis of New Asynchronous Motor Type for Electric Vehicle

2020 ◽  
Vol 24 (7) ◽  
pp. 908-916
Author(s):  
Yong Yan ◽  
Shimin Wang ◽  
Taotao Yang ◽  
Xiangyu Meng ◽  
◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Asynchronous Motor ◽  
Performance Parameters ◽  
Basic Parameters

Based on the dynamic characteristics of electric vehicles, this study describes the use of existing basic parameters of a specific electric vehicle to optimize the performance parameters of an asynchronous motor. In addition, a theoretical reference of such an asynchronous motor is provided.

Design Simulation on Automatic Mechanical Transmission of Electric Vehicle

2013 ◽  
Vol 319 ◽  
pp. 605-609
Author(s):  
Yan Dong Song
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Automatic Transmission ◽  
Drive Train ◽  
Mechanical Transmission ◽  
Vehicle Dynamic ◽  
Vehicle Model ◽  
Overall Performance ◽  
Simulation Results

By optimizing the matching of automatic transmission of car, it could improve the overall performance of electric vehicles. This article analyzes the structure of the electric vehicle drive train, then selects the automatic mechanical transmission combined with the motor-driven features. Then calculate the parameters of motors, batteries, transmission and other parts. The electric vehicle model was created in the Advisor software, then the simulation conditions were selected to test the car, so the vehicle dynamic characteristics and economy were verified by simulation results.

An Incentive-Compatible Combinatorial Auction Design for Charging Network Scheduling of Battery Electric Vehicles

2021 ◽  
pp. 1-18
Author(s):  
Luyang Hou ◽  
Chun Wang ◽  
Jun Yan
Keyword(s):  
New York ◽  
Electric Vehicles ◽  
Dominant Strategy ◽  
Combinatorial Auction ◽  
Network Scheduling ◽  
Winner Determination ◽  
Incentive Compatible ◽  
Battery Electric Vehicles ◽  
Energy Demands ◽  
Charging Stations

Charging network scheduling for battery electric vehicles is a challenging research issue on deciding where and when to activate users’ charging under the constraints imposed by their time availability and energy demands, as well as the limited available capacities provided by the charging stations. Moreover, users’ strategic behaviors and untruthful revelation on their real preferences on charging schedules pose additional challenges to efficiently coordinate their charging in a market setting, where users are reasonably modelled as self-interested agents who strive to maximize their own utilities rather than the system-wide efficiency. To tackle these challenges, we propose an incentive-compatible combinatorial auction for charging network scheduling in a decentralized environment. In such a structured framework, users can bid for their preferred destination and charging time at different stations, and the scheduling specific problem solving structure is also embedded into the winner determination model to coordinate the charging at multiple stations. The objective is to maximize the social welfare across all users which is represented by their total values of scheduled finishing time. The Vickrey–Clarke–Groves payment rule is adopted to incentivize users to truthfully disclose their true preferences as a weakly dominant strategy. Moreover, the proposed auction is proved to be individually rational and weakly budget balanced through an extensive game-theoretical analysis. We also present a case study to demonstrate its applicability to real-world charging reservation scenarios using the charging network data from Manhattan, New York City.

scholarly journals Dynamic Modeling and Vibration Characteristics Analysis of Transmission Process for Dual-Motor Coupling Drive System

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1171
Author(s):  
Wei Fan ◽  
Yongfei Yang ◽  
Xiangang Su
Keyword(s):  
Dynamic Model ◽  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Low Frequency ◽  
Planetary Gear ◽  
Drive System ◽  
Dynamic Responses ◽  
Effective Control ◽  
Analysis Method ◽  
Transmission Process

The dual-motor coupling drive system (DCDS), which is widely used in electric vehicles, has attracted increasing attention due to its high transmission efficiency and economical fuel consumption. Current research has mainly focused on the control scheme of dual motors and has ignored the dynamic characteristics of the asymmetrical transmission structure. This paper presents an investigation of a dynamic model and an analysis method of the transmission process for the DCDS. The entire dynamic model of the DCDS was established by considering the planetary gear, differential bevel gear, and drive shaft with the transfer matrix method (TMM). Then, a detailed theoretical analysis was developed to study the influence of meshing stiffness and excitation source on the dynamic characteristics. Finally, the DCDS experimental platform was utilized to validate the effectiveness of the proposed dynamic model. For susceptibility to low-frequency vibrations, the first four natural frequencies and vibration modes of the DCDS were analyzed through the processing and analysis of acceleration signals. The experimental dynamic responses were generally consistent with the numerically computed results, which demonstrates the effectiveness of the proposed dynamic model with TMM. Furthermore, the proposed dynamic analysis method may be helpful for developing effective control algorithms to suppress vibrations and achieving highly smooth motions for electric vehicles.

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