scholarly journals Testing and Evaluation of the Electric Drive System on the Vehicle Level

2021 ◽  
Vol 12 (4) ◽  
pp. 182
Author(s):  
Zhiguo Kong ◽  
Wei Zhang ◽  
Helin Zhang
Keyword(s):  
Data Acquisition ◽  
Electric Vehicles ◽  
Electric Drive ◽  
Control Strategy ◽  
High Performance ◽  
Test System ◽  
Drive System ◽  
Electric Drive System ◽  
Analysis System ◽  
Testing And Evaluation

In order to obtain the performance of the electric drive system (EDS) on the vehicle level correctly and effectively, the authors carried out research on the testing and evaluation technology. Firstly, the typical control strategy and its influence and limitations regarding the EDS performance were discussed in detail. Secondly, a test system on four-wheel dynamometers with a high-performance data acquisition and analysis system was introduced. A dedicated test was performed. Further analysis of the results was introduced. It is proved that the method introduced here is feasible and effective, which is beneficial to benchmarking and evaluation of the EDS used in electric vehicles.

Research on Energy Management Control Strategy by dSPACE Based Half-Practicality Simulation

2014 ◽  
Vol 697 ◽  
pp. 263-266
Author(s):  
Qun Zhang Tu ◽  
Xiao Chen Zhang ◽  
Ming Pan ◽  
Xia Feng ◽  
Wei Jie Zheng
Keyword(s):  
Energy Management ◽  
Electric Drive ◽  
Control Strategy ◽  
Management Control ◽  
Drive System ◽  
Hardware In The Loop ◽  
Excellent Performance ◽  
Tracked Vehicle ◽  
Electric Drive System ◽  
Working Efficiency

In order to manage the power of electric drive system effectively and improve the fuel economy and working efficiency of electric drive tracked vehicle, this paper proposed a novel energy management control strategy based on the theory of threshold logic and fuzzy logic. The mathematical models of the key components of electric drive system were built in SIMULINK. To examine and analysis the efficiency of control strategy, a driver-controller based HILS (hardware-in-the-loop simulation) platform was built and the energy management control strategy was verified. The simulation results reveal that the strategy have excellent performance in energy distribution, fuel saving and working efficiency, and the proposed control strategy is simple and easy to realize in a real controller, which provides an effective method for the design and application of energy management control strategy of electric drive tracked vehicle.

scholarly journals Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qunzhang Tu ◽  
Xiaochen Zhang ◽  
Ming Pan ◽  
Chengming Jiang ◽  
Jinhong Xue
Keyword(s):  
Power Management ◽  
Electric Drive ◽  
Fuel Economy ◽  
Control Strategy ◽  
Fuzzy Controller ◽  
Management Control ◽  
Drive System ◽  
Tracked Vehicles ◽  
Hybrid Particle Swarm Optimization ◽  
Electric Drive System

This article studies the power management control strategy of electric drive system and, in particular, improves the fuel economy for electric drive tracked vehicles. Combined with theoretical analysis and experimental data, real-time control oriented models of electric drive system are established. Taking into account the workloads of engine and the SOC (state of charge) of battery, a fuzzy logic based power management control strategy is proposed. In order to achieve a further improvement in fuel economic, a DEHPSO algorithm (differential evolution based hybrid particle swarm optimization) is adopted to optimize the membership functions of fuzzy controller. Finally, to verify the validity of control strategy, a HILS (hardware-in-the-loop simulation) platform is built based on dSPACE and related experiments are carried out. The results indicate that the proposed strategy obtained good effects on power management, which achieves high working efficiency and power output capacity. Optimized by DEHPSO algorithm, fuel consumption of the system is decreased by 4.88% and the fuel economy is obviously improved, which will offer an effective way to improve integrated performance of electric drive tracked vehicles.

scholarly journals A Novel Energy Optimization Control Strategy for Electric Drive System Based on Current Angle

2020 ◽  
Vol 10 (11) ◽  
pp. 3778 ◽  
Author(s):  
Jianjun Hu ◽  
Ying Yang ◽  
Meixia Jia ◽  
Yongjie Guan ◽  
Tao Peng
Keyword(s):  
Electric Drive ◽  
Control Strategy ◽  
Golden Section ◽  
Control Object ◽  
General Rule ◽  
Transient State ◽  
Drive System ◽  
Electric Drive System ◽  
Optimization Control ◽  
Overall Efficiency

The combination of permanent magnet synchronous motor (PMSM) and inverter is the key electric drive system (EDS) of electric vehicles (EVs), and its overall efficiency seriously affects the energy consumption of EVs. In order to further improve the efficiency of PMSM-inverter, the influence of a special control object current angle β on EDS was studied and the general rule between β and EDS efficiency was obtained in this paper. Then, the golden section search (GSS) method was used to obtain optimal β and its corresponding stator current is, which can realize EDS working in optimal efficiency in the whole EDS working area. On this basis, an overall efficiency optimization control strategy for EDS based on the current angle β look-up table was proposed in this paper. To verify the effectiveness of the proposed control strategy, simulation considering iron loss and copper loss of motor and inverter loss was completed, which showed that compared with traditional control, the control strategy proposed in this paper can effectively improve the working efficiency of EDS under steady state and transient state.

scholarly journals Research on Control Strategy of Hydraulic Regenerative Braking of Electrohydraulic Hybrid Electric Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghai Zhao ◽  
Hongxin Zhang ◽  
Yafei Xin
Keyword(s):  
Electric Vehicle ◽  
Electric Drive ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Drive System ◽  
Regenerative Braking ◽  
Electric Drive System ◽  
Hybrid Electric ◽  
The Impact

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.

Research on Dynamic Conducted EMI Characteristics of Electric Drive System in Electric Vehicles

2013 ◽  
Vol 773 ◽  
pp. 3-8
Author(s):  
Yan Jie Guo ◽  
Li Fang Wang ◽  
Cheng Lin Liao
Keyword(s):  
Electric Vehicles ◽  
Electric Drive ◽  
Electromagnetic Interference ◽  
Drive System ◽  
Vehicle Speed ◽  
Motor Speed ◽  
Electric Drive System ◽  
Economic Commission ◽  
Simulation And Experiment ◽  
Conducted Emi

This paper represents the conducted electromagnetic interference (EMI) characteristics of the electric drive system in electric vehicles, based on the typical vehicle driving circles. Firstly, the typical vehicle driving circles are introduced, such as Economic Commission of Europe-15 (ECE-15), Extra Urban Driving Cycle (EUDC) and so on. Also, the relationships between motor speed, torque and vehicle speed are calculated according to the mechanical properties of the vehicle. Then, the simulation and experiment platforms are established considering the motor speed and torque as reference inputs. Finally, the dynamic EMI of power electronics device switching processes, system dynamic differential mode (DM) and common mode (CM) EMI are analyzed through the simulation and experiment results.

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