A road gradient and vehicle weight estimator given the driving torque and the wheel speed is developed and validated using a small sized model car in the laboratory. It is shown here that a simple mathematical model of the car is sufficient (including a simple friction model, a model for driving torque and a gravity model due to road gradient) to develop an adaptive, model-based observer. This observer estimates, besides velocity and car position, the mass, friction and road gradient inherent to the car, given driving torque and velocity. Persistent excitation gives theoretical and practical guarantees for accurate estimation of mass and road gradient in addition to the bounded stability guarantees given through Lyapunov theory. For theses tests, a model car system is designed and built to emulate a car system. A test rig consisting, of a 6m long ramp with 3 movable sections, is employed. Each section of the ramp may be angled between and from the horizontal for realistic tests.
|Translated title of the contribution||Hardware in the loop validation of a gradient and weight estimation algorithm and longitudinal speed control using a laboratory model car|
|Title of host publication||International Conference on Systems Engineering (ICSE)|
|Publication status||Published - 2009|