高速履带车辆动力系统仿真模型的实验验证

IF 1 4区 工程技术 Q4 INSTRUMENTS & INSTRUMENTATION
Luka Ponorac, Ivan Blagojević
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引用次数: 0

摘要

高速履带车辆具有复杂的动力系统,除了动力传递和转换外,还具有车辆转向和制动系统的功能,以及车辆上各子系统的供电系统。分析履带车辆的动力平衡,特别是在转弯过程等特定移动场景下的动力平衡,对于了解动力总成部件的动力需求和工作负荷及其优化具有重要意义。为了减少试验测试所需的时间和物力,建立了基于高速履带车辆结构参数的仿真模型。在相同的输入参数和驾驶条件下,对不同的车辆转向工况进行了仿真和实验测试。仿真结果与实验结果进行了对比,验证了仿真模型的准确性。分析所得结果表明,相对转速误差平均值约为5%,相对转矩误差平均值约为7%,相对功率误差平均值约为6.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental Validation of a High-Speed Tracked Vehicle Powertrain Simulation Model
Abstract High-speed tracked vehicles have complex powertrains that, in addition to power transfer and transformation, also perform the functions of vehicle steering and braking systems, as well as power supply system for various subsystems on the vehicle. Analyzing the power balance of a tracked vehicle, especially in specific moving scenarios such as the turning process, is of great importance for understanding the power requirements and workload of the powertrain components and their optimization. A simulation model was developed, based on the construction parameters of an experimentally tested high-speed tracked vehicle to reduce the time and material resources required for experimental testing. Both the simulation and experimental tests were conducted using the same input parameters and driving conditions for different vehicle turning scenarios. Simulation and experimental test results are compared to verify the accuracy of the simulation model. The analysis of the obtained results shows that the average value of the relative rpm error is about 5%, the average value of the relative torque error is about 7%, while the average value of the relative power error is about 6.5%.
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来源期刊
Measurement Science Review
Measurement Science Review INSTRUMENTS & INSTRUMENTATION-
CiteScore
2.00
自引率
11.10%
发文量
37
审稿时长
4.8 months
期刊介绍: - theory of measurement - mathematical processing of measured data - measurement uncertainty minimisation - statistical methods in data evaluation and modelling - measurement as an interdisciplinary activity - measurement science in education - medical imaging methods, image processing - biosignal measurement, processing and analysis - model based biomeasurements - neural networks in biomeasurement - telemeasurement in biomedicine - measurement in nanomedicine - measurement of basic physical quantities - magnetic and electric fields measurements - measurement of geometrical and mechanical quantities - optical measuring methods - electromagnetic compatibility - measurement in material science
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