Performance analysis of a grade estimation method by means of simulation

Digital maps allow advanced driver assistance systems to adapt their behavior to the vehicle's surroundings. Preview grade information can be used in on-board functions of a heavy duty vehicle such as adaptive lighting, predictive cruise control and gearbox control. These functions have a potential for adding safety, increasing fuel eciency and improving driver comfort. Grade estimation by use of existing inexpensive on-board sensors in heavy vehicles is a promising way of creating and maintaining up-to-date road grade maps with minimal investment. This thesis examines the performance of a recently developed grade estimation method. Simulation is used to test the grade estimation performance in a longer perspective than is possible with the experimental data currently available. Errors are introduced into the simulation model based on interviews and experience from road tests of the estimation method. Fast convergence is seen when many simulated runs are fused into a grade map. Also, experimental data are analyzed and some systematic errors are found in the vehicle model. These errors are not explicitly accounted for in the error model for vehicle data used in the grade estimation method. By comparing grade estimated with the aid of GPS to grade calculated using only vehicle data, corrections to the vehicle model are computed. The eect of these corrections is examined and it is shown that it is feasible to take dynamic parameter errors into account in an estimation method with a potential for increased performance. For a heavy vehicle a decrease of 45% in the residual error of fused grade estimates is observed when adding these corrections. Candidates for a method that integrates this new knowledge of model errors into a grade estimation method are proposed. Obtained knowledge of the dynamic vehicle behavior may also be valuable in applications using the generated grade data