Abstract-This paper considers the problem of eco-driving for electric cars. This problem is formulated as an Optimal Control Problem (OCP) aiming at minimizing the vehicle's energy consumption over fixed time and distance horizons. The impact of battery parameter variations and auxiliary power demands on the optimal vehicle velocity computation are studied from a model complexity viewpoint. Simulation results are presented and discussed to illustrate the suggested simplifications.

Abstract-In this paper, two simplified methods based on Dynamic Programming (DP) to solve an Eco-driving problem for a conventional vehicle equipped with an internal combustion engine are studied. The first method is based on the transformation of a time-based Optimal Control Problem (OCP) into a distance-based OCP while the second is based on solving the time-based OCP directly. The Pontryagin Minimum Principle (PMP) is used to decrease the complexity of the OCP formulation. Based on simulations, the two methods are compared in terms of optimality (fuel consumption) and the time needed to run the DP. The impact of the mesh choice on the optimality of the solution is also investigated.

In this paper, the problem of eco-driving for a conventional vehicle equipped with an internal combustion engine is studied. The associated optimal control problem is formulated and solved using Dynamic Programming (DP). The impact of the mesh choice on the optimality of the DP solution is investigated in order to find a trade-off between the optimality of the DP solution and its computation time. The eco-driving speed trajectories obtained were tested on a high-frequency HIL (Hardware-In-theLoop) engine test bench to quantify the real reductions in fuel consumption. Simulations and experiments are compared.

In this paper, the calculation of eco-driving cycles for a Hybrid Electric Vehicle (HEV), using Dynamic Programming (DP), is investigated from the solving method complexity viewpoint. The study is based on a comparative analysis of four optimal control problems formulated using distinct levels of modeling. Starting with three state dynamics (vehicle position and speed, battery state-of-charge) and three control variables (engine and electric ma-* Corresponding author.