Backcasting of Transport Electrification and Efficiency Policies Through Optimal Control

Abstract

This study presents a backcasting approach applied to the decarbonization of the passenger car fleet in Metropolitan France. Three policy measures are considered, namely, EV purchase incentive, Malus CO2 , and eco-driving (ED) incentives. Through a forecasting model, their impacts are separately evaluated in terms of market shares and emissions. An optimal control problem is then formulated to determine the combined policy trajectory that minimizes monetary cost and reach a defined CO2 target. A Pareto front is evaluated, along which costs to achieve lower CO2 targets increase. The results suggest that EV incentives should decrease over time and be inversely proportional to the income class, the Malus CO2 should be kept for a longer time at its maximum value, while the more effective ED incentive should cover as much population as possible.