Potential analysis of predictive optimal velocity control for electric and conventional vehicles

Abstract

Optimizing the velocity of a vehicle over a known future route can reduce fuel consumption. This article studies the potential fuel-savings of such systems for conventional vehicles, employing an internal combustion engine, and its application to electric vehicles.A main drawback of many optimization algorithms is their computational complexity, which prevents them from being used in real-time applications. To overcome this drawback a fast algorithm is presented to optimize the velocity of a vehicle with known route slope. Using this algorithm the consumption for five real world scenarios is simulated and compared against a constant velocity policy.The results achieved for the conventional vehicle are comparable to real-world results reported in other articles and offer about 20% fuel saving using free-wheeling compared to driving with a constant velocity. For electric vehicles the consumption savings, which can be achieved using free-wheeling lie around 3.5%.

Look-ahead controls of heavy duty trucks on open roads — six benchmark solutions

“…The Optimizer uses a multi-objective approximate dynamic programming scheme to calculate the next gear and velocity profile for minimizing fuel consumption as described in Vögele and Endisch (2016). Given the current vehicle state x x x,consisting of its velocity v and the current gear u g…”

“…Dynamic Programming is often proposed to improve the fuel economy of vehicles, by automating their longitudinal behavior. Examples of such controllers are given in Radke (2013); Themann et al (2014b,a); Vögele and Endisch (2015). A property of Dynamic Programming is that it can find the globally optimal solution for a scenario.…”