scholarly journals Design and Modeling of a Test Bench for Dual-Motor Electric Drive Tracked Vehicles Based on a Dynamic Load Emulation Method

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 1993 ◽  
Author(s):  
Zhe Wang ◽  
Haoliang Lv ◽  
Xiaojun Zhou ◽  
Zhaomeng Chen ◽  
Yong Yang
Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 77 ◽  
Author(s):  
Christoph Datlinger ◽  
Mario Hirz

Due to the increasing electrification of automotive drive train systems, accurate position and speed sensors play an important role to achieve an optimum drive train performance and driving range. These sensor systems determine the rotor shaft position to deliver exact data for efficient drive train control. The system itself must be reliable, sufficiently accurate and cost efficient at the same time. In this way, the design process of the sensor system is influenced by a trade-off, which influences the system performance in view of different parameters, e.g., resolution and data processing accuracy. The focus of the present work is to introduce a method for benchmarking the performance of not only the rotor shaft position sensor, but the whole electric drive train sensor systems by use of a highly accurate reference system on a specifically developed test bench. To achieve a significant benchmark statement by determination of the rotor position angle error, the independent measuring systems, the automotive drive train system and the reference system are synchronized by the use of a common trigger/clock signal. The mentioned signal defines the time steps of the system under test rotor position angle capturing procedure and those of the reference system simultaneously. This enables a common time-base for two independent working measurement systems. This publication provides information about a concept for enhanced rotor position sensor evaluation that enables the merging of real-time data processing with test bench measurement. This procedure provides an important basis for the selection and optimization of position sensor systems for sophisticated electric powertrains.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qunzhang Tu ◽  
Xiaochen Zhang ◽  
Ming Pan ◽  
Chengming Jiang ◽  
Jinhong Xue

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.


2014 ◽  
Vol 644-650 ◽  
pp. 943-946
Author(s):  
Shuai Mou ◽  
Zhi Ping Chen ◽  
En Dao Xu ◽  
Jia Lei Jin ◽  
Jing Tong

In order to testify the driving characteristics of 3m homemade steel-belt friction drive test bench, a data detection system under AT89C52 is developed.The system uses two photoelectric encoders as the speed testing unit and one weighing sensor as the strength testing unit.therefore.It is critical to both of them to be used on real time to detect properties,such as rotation speeds, direction, pre-tightening force and dynamic load and so on. It is tested that this system is stable which can record the date of pre-tightening force accurately with the error in the range of 1% and keep transmission accuracy with the error in the range of 0.5%.


2018 ◽  
Vol 10 (1) ◽  
pp. 168781401774966
Author(s):  
Ming-Fei Gao ◽  
Ji-Bin Hu ◽  
Zeng-Xiong Peng

This article focus on the configuration synthesis of electric-drive transmissions for tracked vehicles. First, a new graph theory model is proposed to represent the transmission mechanism, which makes the complex transmission system easier to understand. Second, a configuration synthesis method is proposed based on kinematics and statics, in which the speed degree of freedom and torque degree of freedom are considered as the constraints of configuration synthesis. Also, the expressions for speed degree of freedom and torque degree of freedom are derived. Third, based on the graph theory model, the necessary condition to achieve skid steering in the transmission of tracked vehicles is obtained. The results of this article can provides a theoretical basis for the design and analysis of transmission mechanism of tracked vehicles.


2019 ◽  
Vol 9 (12) ◽  
pp. 2480
Author(s):  
Zhaomeng Chen ◽  
Xiaojun Zhou ◽  
Zhe Wang ◽  
Yaoheng Li ◽  
Bo Hu

Dual-motor electric drive tracked vehicles (DDTVs) have drawn much attention in the trends of hybridization and electrification for tracked vehicles. Their transmission chains differ significantly from the traditional ones. Due to the complication and slug of a traditional tracked vehicle braking system, as well as the difference of track-ground with tire-road, research of antilock braking control of tracked vehicles is rather lacking. With the application of permanent magnet synchronous motors (PMSMs), applying an advanced braking control strategy becomes practical. This paper develops a novel emergency braking control strategy using a sliding mode slip ratio controller and a rule-based braking torque allocating method. Simulations are conducted under various track-ground conditions for comparing the control performance of the proposed strategy with three other strategies including the full braking strategy, traditional antilock braking strategy, as well as sliding mode slip ratio strategy without the use of motors. For an initial speed of 80 km/h, simulation results show that the proposed control strategy performs the best among all strategies mentioned above. Several hardware-in-the-loop (HIL) experiments are conducted under the same track-ground conditions as the ones in the simulations. The experiment results verified the validity of the proposed emergency braking control strategy.


2020 ◽  
Vol 11 (2) ◽  
pp. 267-283
Author(s):  
Mingxi Bao ◽  
Xiangdong Ni ◽  
Xin Zhao ◽  
Shen Li

Abstract. To improve the HMCVT gear shifting smoothness of the self-propelled cotton picker, the quadratic orthogonal rotation test was carried out through the HMCVT test bench and control system with engine speed, clutch oil pressure, flow control valve, load torque, displacement ratio as the influencing factors while jerk, dynamic load coefficient, speed drop, weighted acceleration RMS, frictional work as the response indexes. The mathematical model between the response indexes and the influencing factors was established through the data processing software Design Expert 10. After the single factor and multi-factor experimental analyses, the parameters were optimized based on the response surface methodology to obtain the optimal parameters. The test was carried out on the HMCVT test bench with the optimized parameter combination. The engine output speed was 900 rpm, the clutch oil pressure was 3.5 MPa, the flow control valve was 4.9 L min−1, the load torque was 130 Nm and the displacement ratio was −0.93. The result was as follows: the jerk was 5.04 m s−3, the weighted acceleration RMS was 0.467, the speed drop was 20.32 rpm and the dynamic load coefficient was 12.16. This study provides reference for the smooth shifting of the self-propelled cotton picker, which is of a certain significance to promote the operation of the self-propelled cotton picker under multiple working conditions.


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