首页|基于混合模型的特种车辆转向泵马达性能评估

基于混合模型的特种车辆转向泵马达性能评估

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为了实现转向泵马达运行性能的实时评估,首先构建了转向泵马达物理模型,该模型考虑了转向泵马达运行机理,通过求解泵马达外特性方程、液压回路平衡方程、内部流量计算方程等,实现内部不可测参数的初步评估与计算,进而获得各类参数对转向泵马达性能的影响机制.同时采用LSTM深度学习方法构建了转向泵马达数据驱动模型,学习并预测不同工况下转向泵马达容积效率的变化规律,并将其输入至物理模型形成转向泵马达性能评估混合模型,提高不同工况条件下转向泵马达性能评估的准确性及适用性.实例分析表明,该混合模型可实现复杂工况下转向泵马达高低压侧压力、流量、转速及转矩等参数的计算与评估,模型误差低于10%.
Performance Evaluation of Special Vehicle Steering Pump Motor Based on Hybrid Model
To realize real-time evaluation of the steering pump motor's operating performance,a physical model of the steering pump motor is firstly constructed in this paper,which considers the operating mechanism of the steering pump motor.By solving the pump motor's external characteristic equation,hydraulic circuit balance equation,and internal flow calculation equation,etc.,the preliminary evaluation and calculation of the internal unmeasurable parameters can be realized.Then,the influence mechanism of various parameters on the performance of the steering pump motor is obtained.At the same time,LSTM deep learning method is used to build a data-driven model of the steering pump motor to learn and predict the variation rule of the volume efficiency of the steering pump motor under different working conditions.The volume efficiency is then input into the physical model to form a mixed model of steering pump motor performance evaluation,so as to improve the accuracy and applicability of steering pump motor performance evaluation under different working conditions.The example analysis shows that the hybrid model can calculate and evaluate the internal and external parameters such as internal pressures,flow rate,speed and torque of the steering pump motor with high accuracy under complex working conditions,and the model error is less than 10%.

steering pump motorhybrid modelperformance evaluation

李乐、米雨欣、贾然

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北京信息科技大学 机电工程学院,北京 100192

转向泵马达 混合模型 性能评估

国家自然科学基金资助项目国家"173"计划项目北京市教委科研计划科技一般项目

52175074MKF20210009KM202311232006

2024

湖南大学学报(自然科学版)
湖南大学

湖南大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.651
ISSN:1674-2974
年,卷(期):2024.51(8)
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