Optimal Stochastic Eco-Routing Solutions for Electric Vehicles

Efficient Energy-Optimal Routing for Electric Vehicles

Traditionally routing has focused on finding shortest paths in networks with positive, static edge costs representing the distance between two nodes. Energy-optimal routing for electric vehicles creates novel algorithmic challenges, as simply understanding edge costs as energy values and applying standard algorithms does not work. First, edge costs can be negative due to recuperation, excluding...

Optimal Routing for Plug-In Hybrid Electric Vehicles

We propose routing algorithms for plug-in hybrid electric vehicles (PHEVs) that account for the significant energy efficiency differences of vehicle operating modes and recommend the predominant mode of operation for each road segment during route planning. This is to enhance fuel economy and reduce emissions. We introduce the Energy-Efficient Routing problem (EERP) for PHEVs, and formulate thi...

Energy-Optimal Routing with Turn Costs for Electric Vehicles

This bachelor thesis focuses on the integration of turn costs in route planning for electric vehicles. First the information provided by the PHEM [HRZL09] data is used to create consumption values for turn costs. An accordingly appropriate matching principle is described to link costs of brake or acceleration maneuvers extracted from this data to turns in graphs representing road networks. Next...

The Shortest Path Problem Revisited: Optimal Routing for Electric Vehicles

Stochastic Optimal Control of Parallel Hybrid Electric Vehicles

Energy management strategies (EMSs) in hybrid electric vehicles (HEVs) are highly related to the fuel economy and emission performances. However, EMS constitutes a challenging problem due to the complex structure of a HEV and the unknown or partially known driving cycles. To meet this problem, this paper adopts a stochastic dynamic programming (SDP) method for the EMS of a specially designed ve...