Versatile Cruise Control with Fuzzy Logic: A Comparative Analysis of Industry-Ready Approaches with Fuel Consumption Considerations

Traditional cruise control algorithms struggle to adapt to diverse vehicle types due to variations in parameters such as mass, engine power, aerodynamic drag coefficient, and transmission characteristics. These challenges often require heuristic tuning of PID controllers for each vehicle model. This paper presents a comparative analysis of two approaches based on fuzzy logic to address this limitation. The first approach uses fuzzy logic to tune PID parameters at the outset for each vehicle, enabling independent operation of multiple switching PID controllers without the need for further tuning. The second approach introduces a continuously operating fuzzy-based PID controller, which eliminates the need for mode-switching. Simulations performed using the ADVISOR vehicle model validate both methods, demonstrating enhanced adaptability and responsiveness under various driving conditions. A comprehensive case study evaluates the stability, performance, computational efficiency, and fuel consumption of a representative vehicle, showcasing the potential for market-ready implementation.