Estimation of Vehicle Longitudinal Dynamic Parameters through Hardware in the Loop Simulation

Appropriate control of the vehicle longitudinal dynamic requires accurate and real-time knowledge of the parameters affecting the dynamics of the vehicle. The main contribution of this paper is in developing an estimator called short-time linear quadratic form (STLQF) which is a new parameter estimation technique to simultaneously estimate the time-varying parameters that affect on vehicle longitudinal dynamics with a low latency. These parameters are the vehicle mass, time varying road slope angle and overall aerodynamic drag coefficient of the vehicle in real time. Next, the efficiency of STLQF algorithm is shown by comparing the results of STLQF technique in an experimental test against the recursive least squares (RLS) parameter estimation method. The results of implementing STLQF parameter estimation algorithm, showes the better performance of STLQF estimator compared with RLS algorithm. In the end, the STLQF estimator is simulated in hardware in the loop configuration using an AVR microcontroller in order to rapid prototype of the STLQF method by minimum cost and high accuracy in the least possible time.