Signal Estimation for Vehicle Body Accelerations Using Piecewise Linear System Identification in the Frequency Domain

Abstract

In this work, we investigate a signal estimation problem which is common and critical for durability design of vehicle bodies. The relation between the frequency responses of accelerometers is the target to model so that the ones of easy-to-measure accelerometers can estimate the responses of hard-to-measure accelerometers. A piecewise linear frequency-domain identification method relying on finite impulse response (FIR) models is proposed and performed to tackle the nonlinearity issue in the signal estimation problems: first, the interesting frequency range is segmented into three subranges which are clearly identified by peak histograms of frequency signals. Then, FIR models which provide a satisfactory description of the system are constructed to estimate the frequency responses of the interesting signals at subranges, one for each. The performance of the proposed approach is validated by using real-world data under multiple working conditions. The results show that the proposed method has a good estimation accuracy, and it brings the benefit that the number of accelerometers can be significantly reduced during the durability design of vehicle bodies.