The Synthetic 3DOF Wheel Force for Passenger Vehicle Based on Predicted Frequency Response Function Model

TL;DR: In this article, an effective approach of wheel force prediction by using the frequency response function (FRF) model of vehicle dynamic system is described, and the quality evaluation of prognostication results is made by comparing the synthetic and real-world wheel force signals in time/frequency domain and frequency related pseudo damage.

Abstract: To determine the vehicle chassis requirements, wheel force transducer (WFT) have been the best option when it is being used in targeting customer correlation or determining the effective use of the proving ground. However, using wheel force transducer in customer correlation fleet test is often unfeasible due to the huge cost and low practicability. As a result, engineers have to choose other transducer measures. This paper describes an effective approach of wheel force prediction by using the frequency response function (FRF) model of vehicle dynamic system. A vehicle system linear modelling technique is used. For the system identification of FRF, the acceleration and wheel force time history data, as system input and output, are collected from an instrumented passenger car as it traverses in different real-world proving ground surfaces. The obtained FRF represents the complex suspension mechanical model. Once the FRF is calculated, the predicted force signal can be implemented. The quality evaluation of prognostication results is made by comparing the synthetic and real-world wheel force signals in time/frequency domain and frequency-related pseudo damage. The result indicates that the FRF derived from realworld data is an effective modelling tool. Furthermore, it is a promising application in the field of customer usage fleet test and suspension dynamic system modelling or control. Introduction Wheel force transducer has been widely proven in the modern development process of the worldwide automotive industry as the most effective approach for the vehicle spindle dynamic force acquisition. The accurate input load benefits the FEA engineer in suspension, body/ frame durability evaluation [1, 2, 3, 4]. However, the implement of a WFT-involved road test is undoubtedly a time-consuming process, which means if the engineer needs strong confidence about the collected data one should consider the unsprung mass deviation, wheel balancing, and measurement plane in practical engineering [5, 6]. In addition, the design, calibration and manufacturing process make the WFT a relatively high price [7, 8]. Due to these reasons, the sensor is suitable for accurate road load data acquisition (RLDA) in proving ground instead of massive application in public road load data acquisition. When the engineering problem presents on our test planner’s desktop, the application of wheel force transducer in fleet test level is definitely not a rational option. It is beneficial to develop a force prediction tool as a substitution of wheel force transducer in an acceptable accuracy and price [9]. In the field of customer correlation, wheel axle load is treated as primary correlation factor in the process of mathematical optimization. The common engineering techniques are David’s Integrated Durability Engineering, Dressler’s Reference-Customer-Spectrum and Andrew’s Relative Damage Spectrum [10, 11, 12]. In the field of dynamic force reconstruction, Dobson discussed the theoretical technique used in the calculation of excitation force [13], however it states that the disadvantage of frequency domain model had prediction problems in the region of anti-resonances. In the work of Cornelis, it suggests a force prediction technique which is Augmented Kalman Filter virtual sensing [14]. The deficiency of their current work is that only constant frequency sinusoidal input forces were being discussed and the prediction is a simulation in numerical environment. This paper will explore the feasibility study of the FRF modelling method in durability and reliability. We first give a brief description of our prediction model architecture, then describe the creation of the modelling datasets and the data pre-processing. We conclude by summarizing the results obtained in the prediction model. Technique Background For most experimental modal analysis, the impact force ordinarily acts as inputs and acceleration acts as outputs [15]. However, in our case, to build a force prediction model, we treat the wheel center acceleration as inputs and wheel force as outputs. To prove the feasibility of such hypothesis, an argument is made in the following passage. As a quarter car Downloaded from SAE International by CATARC, Monday, June 21, 2021