A Feasibility Study on Driver Model Based Lap Time Simulation Using Genetic Algorithms
Abstract Lap time simulation has always been a topic of interest in the automotive industry as it summarizes the whole dynamic performance of an automobile in a single value. During the development of road and race cars, to avoid expensive testing and to prove different design solutions, it is useful to simulate the maximum performance of the vehicles. The cars are driven to their limits to exploit their capabilities, where their dynamic behaviour can be highly non-linear. The vehicle models need to replicate these characteristics as precisely as possible. Due to this, the problem of achieving the minimum lap time with a certain car around a race track is a challenging problem to solve. A method to evaluate the minimum lap time is presented, approaching the optimal solution by coupling a driver model, a simulation environment and genetic algorithms to perform the optimization. The algorithm also offers the possibility to add vehicle parameters to be optimized regarding the lap time.