Least costly energy management for Electric Vehicles with plug-in Range Extenders

Abstract

Electric Vehicles (EVs), though appealing for an increasing number of users, suffer from known limitations of battery energy storage. We analyze a rentable plug-in Range Extender (RE) concept as a viable way to increase the EV range only when really needed, avoiding its encumbrance in normal urban usage. This concept leads to the formulation of an original energy management problem: in addition to usual operating constraints, the rental decision must be taken in the least costly way from the user's perspective. The original problem is solved offline by Dynamic Programming to provide the best achievable performance; a mixed integer convex reformulation is shown to yield the same results in much less time. The performance is compared by means of a thorough simulation study.

Control of connected and automated vehicles: State of the art and future challenges

“…Instead of minimizing only energy consumption, several authors have addressed also different optimization goals, such as pointwise powertrain efficiency [106], drivability [107], pollutant emissions [63,108], battery aging [109,110,111], driving cost [112,113,114,115]. The MPC approach in [116], instead, combines longitudinal control and energy management, exploiting forecasts of traffic signals and road slope.…”

“…The two approaches yield very similar performance and clearly outperform the CDCS approach. A similar problem is considered in [114,115], for a modular plug-in hybrid electric vehicle, in which an engine and a generator are mounted on a trailer that can be detached from the main electric vehicle. In the analyzed scenarios, the trailer can be rented at fixed locations along the route, with different fuel and pricing options.…”

Optimal energy management in series hybrid electric bicycles

“…The main analytical tool in [1] is Pontryagin's Minimum Principle, which has also been used for HEV energy management (see e.g. the ECMS [5,7] and the least costly approach [34][35][36][37]). The Minimum Principle gives the analytical expressions of the Hamiltonian H, of the adjoint states derivativesṗ 1 ,ṗ 2 ,ṗ 3 and of their boundary conditions p 1 (T ), p 2 (T ), p 3 (T ).…”