Road Slope Estimation Using a Longitudinal Accelerometer and Kalman Filtering
Abstract: Heavy-duty vehicles of today consist of much electronics and many sensors. One of these sensors is a longitudinal accelerometer. This Master's thesis investigates the possibilities to determine the road slope angle with a longitudinal accelerometer. With the knowledge of current road slope angle, many other control systems in the trucks can be improved. The optimization of these control systems are important in order to maximize safety and minimize fuel consumption. The work consisted of developing an observer for estimating the road slope angle and tuning it until the results were satisfying. The estimations are made with a Kalman filter. Improvements obtained with fixed lag smoothing are also investigated. The results obtained in the thesis show that the road slope angle can be estimated with a longitudinal accelerometer. The results are satisfying, except during powerful retardations. A solution for improvement in these scenarios is presented. The solution consists of changing the dynamics of the estimations when a retardation is detected.
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