2014IEEE PES Innovative Smart Grid Technologies EuropeRequires access

Charging optimization of battery electric vehicles including cycle battery aging

Annette Trippe, Raghavendra Arunachala, Tobias Massier, Andreas Jossen, Thomas Hamacher

Open publisher page 44 citations

Abstract

Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

About this research paper

What this paper is about

Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

Why it matters

OpenAlex reports 44 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

Key concepts: Battery (electricity), Automotive battery, Charge cycle, Automotive engineering, Trickle charging, Electricity, Electric-vehicle battery, Electric vehicle

Related papers

Back to paper searchBrowse research topicsOriginal source
Charging optimization of battery electric vehicles including cycle battery aging — Research Paper | ScholarLens