Optimal predictive eco-driving cycles for conventional, electric and hybrid electric cars

In this paper, the computation of eco-driving cycles for electric, conventional, and hybrid vehicles using receding horizon and optimal control is studied. The problem is formulated as consecutive-optimization problems aiming at minimizing the vehicle energy consumption under traffic and speed constraints. The impact of the look-ahead distance and the optimization frequency on the optimal speed computation is studied to find a tradeoff between the optimality and the computation time of the algorithm. For the three architectures considered, simulation results show that in urban driving conditions, a look-ahead distance of 300–500 m leads to a sub-optimality less than $1\%$ in the energy consumption compared to the global solution. For highway driving conditions, a look-ahead distance of 1–1.5 km leads to a sub-optimality less than  $2\%$ compared to the global solution.