Prediction-oriented fuzzy logic approach to autonomous braking activation in electric vehicles under a time headway-based spacing policy

Regenerative Braking Systems (RBS) in Electric Vehicles (EVs) generate electricity during coasting, yet energy recovery can be reduced when friction brakes are used prematurely. This paper investigates an autonomous braking control strategy for EVs based on Fuzzy Logic (FL) by incorporating a time-headway spacing policy to improve energy recovery during deceleration. Using relative distance and relative speed, a headway-based spacing rule is enforced to decide friction-brake activation. This rule is set to prioritise coasting and regenerative braking whenever possible. The control system is implemented in MATLAB/Simulink on an electric go-kart model and benchmarked against a baseline FL controller without safe-distance gating across three lead-vehicle scenarios. The first scenario is a constantly slower lead vehicle (with varying initial gaps); the second involves gradual deceleration, and the third involves sudden deceleration. Simulation results demonstrate that the proposed strategy reduces peak brake force, shortens total braking duration by over 50%, and often eliminates unnecessary friction-brake usage. Maximum deceleration also decreased by up to 46.1%, coasting distance increased by approximately 1.95%, and energy recovery improved by 21.7%. In genuine emergency braking situations, both controllers (with and without prediction) produce equivalent behaviour, demonstrating that energy-aware braking is achieved without compromising safety.