Virtual Method for Electronic Stop-Start Simulation & VDV Prediction Using Modified Discrete Signal Processing for Short Time Signals

Electronic Stop-Start (ESS) system automatically stops and restarts the engine to save energy, improve fuel economy and reduce emissions when the vehicle is stationary during traffic lights, traffic jams etc. The stop and start events cause unwanted vibrations at the seat track which induce discomfort to the driver and passengers in the vehicle. These events are very short duration events, usually taking less than a second. Time domain analysis can help in simulating this event but it is difficult to see modal interactions and root cause issues. Modal transient analysis also poses a limitation on defining frequency dependent stiffness and damping for multiple mounts. This leads to inaccuracy in capturing mount behavior at different frequencies. Most efficient way to simulate this event would be by frequency response analysis using modal superposition method. In order to do the same, there is a major hurdle which is due to the nature of the signal being highly transient and of short duration, this event is difficult to be captured in frequency domain. Traditional FFT techniques used for domain transformation are not accurate enough to capture and transform these short duration events from time domain to frequency domain and vice-versa. Simulation in frequency domain helps in interpreting the effects of modal interactions and resonances. It also helps in providing enablers to mitigate issues and use frequency dependent stiffness for mounts and appropriate damping. This paper focuses on providing a comprehensive method to capture this short duration transient ESS start event in frequency domain accurately, by using Discrete Fourier Transform (DFT) along with additional modifications to the mathematical formulation. This paper also highlights the boundary conditions required to accurately simulate this event for different suspension architectures for instance solid axle suspensions and independent suspensions. Finally, this paper also showcases test vs virtual correlation case studies for ESS virtual analysis of a full vehicle system with different suspension architectures.