Design and implementation of dynamic parameter adaptive tracking controller with unknown vehicle parameters

This paper investigates longitudinal adaptive cruise control for electric vehicles, focusing on the effects of unknown parameters at low speeds. We introduce a dynamic parameter adaptive control (DPAC) algorithm to enhance robustness in real-world vehicle-following scenarios where existing controllers are insufficient. Initially, we perform theoretical analysis and design of the vehicle model and controller to establish the speed control system. Subsequently, both the vehicle system and controller are discretized for validation. Finally, we conduct simulations and experimental tests on an electric vehicle equipped with the DPAC. The results demonstrate that the proposed DPAC significantly improves vehicle-following performance compared to existing approaches.