Abstract
To benchmark a hybrid vehicle’s Energy Management Strategy (EMS) usually a given, often certified, velocity trajectory is exploited. In this paper it is reasoned that it is also beneficial to optimize the velocity trajectory. Especially optimizing the vehicle braking trajectories, through maximization of energy recuperation, results in considerable fuel savings on the same traveled distance. Given future route (target velocities as function of traveled distance/location), traffic, and possibly weather information, together with the vehicle’s road load parameters, the future power request trajectory can be estimated. Dynamic Programming (DP) techniques can then be used to predict the optimal power split trajectory for the upcoming route, such that a desired state-of-charge at the end of the route is reached. The DP solution is re-calculated at a certain rate in order to adapt to changing conditions, e.g. , traffic conditions, and used in a lower level real-time EMS to guarantee both battery state-of-charge as well as minimal fuel consumption.
Highlights
A hybrid vehicle employs several power converters instead of one
The objective outlined in this paper is to find a real-time implementable Energy Management Strategy (EMS), which has no exact knowledge of the future power trajectory, but, still minimizes fuel consumption
The remainder of this paper is organized as follows: first, the vehicle dynamics are discussed; Section 2 discusses the vehicle mass and road load parameter variations, in Section 3 the construction of a future power trajectory is outlined; Section 4 describes the proposed EMS; in Section 5 a numerical example is presented; we summarize with conclusions and give an outlook of future work
Summary
Résumé — Optimisation de la gestion de l’énergie dans des véhicules poids lourds électriques hybrides utilisant le guidage d’itinéraire – Pour évaluer la Stratégie de Gestion de l’Énergie (SGE) d’un véhicule hybride, on exploite généralement un cycle de conduite donné, souvent certifié. Pour un itinéraire donné (vitesses cibles en fonction de la distance parcourue et de la position), compte tenu des conditions de circulation, des éventuelles données météorologiques et des paramètres de perte du véhicule, on peut estimer les besoins en puissance nécessaire pour le parcourir. La solution est recalculée périodiquement afin de l’adapter aux nouvelles conditions du parcours (par exemple, aux conditions de circulation) et est utilisée dans une couche plus basse de la SGE en temps réel pour garantir l’état de charge de la batterie ainsi que la consommation d’essence minimale. Abstract — Optimal Energy Management in Hybrid Electric Trucks Using Route Information — To benchmark a hybrid vehicle’s Energy Management Strategy (EMS) usually a given, often certified, velocity trajectory is exploited. Given future route (target velocities as function of traveled distance/location), traffic, and possibly weather information, together with the vehicle’s road load parameters, the future power request trajectory can be estimated. The DP solution is re-calculated at a certain rate in order to adapt to changing conditions, e.g., traffic conditions, and used in a lower level real-time EMS to guarantee both battery state-of-charge as well as minimal fuel consumption
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