Parametric analysis of human vertebrae towards vibration impacts from electric vehicle steering system - Muhammad Azrai bin Amir (Kulliyyah of Engineering, International Islamic University Malaysia, 2017)
With the importance of reducing carbon footprint and minimizing air pollution, the introduction of electric vehicle (EV) is tipped to be the next best alternative. EV's feature of zero carbon emission is highly appraised. In effort to improve the EV more advance specifications are installed such as Electric-Powered Assist Steering System (EPAS). The cutting-edge steering system technology is getting popular in automotive industry. It is said and proven to ease and resolve the difficulty that the conventional hydraulic steering system encountered before. The absence of hydraulic system parts such as power steering pump and hydraulic fluid, EPAS gives positive effects for the user with its easy maintenance and lesser weight added to the overall car system. Although with presence of many advantages of EPAS over hydraulic steering system, it is still prone to induce vibration impacts that affect the driver and passengers. Thus, it exhibit driver's discomfort and increase fatigue level at low frequency vibration happens. In addition to the bad impact stated before, road condition is also one of the key factors that needed to be taken into consideration. The impact can be felt by the occupant of the vehicle. Low frequency vibration causes stress in the lumbar muscles, where it can lead to discomfort and fatigue around perception threshold towards the person sitting on the vehicle. The negative impacts are worsening during long distance driving. Thus, optimization of vibration is the goal for this research. First method done is data sampling from long distance driving process and repeated laps for short distance driving. Both style of driving are observed for the human vertebrae response towards the vibration. Because of low frequency vibration, data filtration is required to eliminate unwanted trace from the overall signal. Using a few selected model structures such as Autoregressive Models with Exogenous Inputs (ARX), Autoregressive–Moving-Average Model (ARMAX), Box-Jenkins and Output-Error from system modeling and identification technique, the effect of vibration can be minimized. It is proven that modeling using ARX technique with high order output is the best compared to other selected model structures.