A multi-objective regenerative braking control strategy combining with velocity optimization for connected vehicles

Deceleration is unavoidable owing to the traffic lights or obstacles during driving, which lead to great energy dissipation. To promote energy utilizing efficiency, regenerative braking is applied to convert kinetic energy into electricity. Previous researches about regenerative braking concentrate on the braking torque allocation optimization, which is undoubtedly important. Moreover, the control performance can be further improved combining with velocity optimization. With the emerging Connected Vehicle Technology, environmental information is available for vehicles. Therefore, the terminal braking distance and terminal velocity can be derived utilizing the information. Then a multi-objective regenerative braking control strategy based on the pesudospectral method is proposed with the terminal constraints. The control strategy optimizes both the velocity and braking torque allocation to reduce the energy dissipation and battery capacity loss simultaneously. Simulations are carried out under a speed bump scenario. Pareto front is obtained with different weights of the objectives and then analyzed to reveal the tradeoff between energy recovery and battery health, which assists in finding a desired balanced solution. Two representative Pareto optimal solutions are selected for comparison: the energy recovery priory strategy and the energy-life tradeoff strategy. Compared with the energy priory strategy, the energy-life tradeoff strategy decreases the battery capacity loss by 60.65%, but it leads to a 36.07% reduction in the energy recovery.