4.8 Article

Open Source Algorithm for Smart Charging of Electric Vehicle Fleets

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 17, Issue 9, Pages 6014-6022

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3038144

Keywords

Algorithm; electric vehicles (EVs); open source; practical validation; smart charging

Funding

  1. German Federal Ministry for Economic Affairs and Energy [TII-20-2703]

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Smart charging involves assigning charging capacities between vehicles in limited infrastructures and can now be found in both commercial and open source solutions. This article introduces an open source package with a smart charging algorithm and presents implementation aspects and field test results showing its effectiveness. By scheduling vehicles for charging while ensuring fair share, the smart charging algorithm has demonstrated real-time applicability and scalability to large fleet sizes.
Smart charging assigns charging capacities between vehicles in limited charging infrastructures. Smart charging solutions are becoming widespread with increasing numbers of commercial offerings. However, commercial solutions are intransparent regarding algorithm implementation. In contrast, open source solutions are transparent and open for collaborative development and scientific research. This article presents an open source package with a smart charging algorithm. The algorithm schedules heterogeneous fleets of vehicles for charging while ensuring a fair share for each vehicle. We present implementation aspects of the smart charging algorithm including data structures and representational state transfer application programming interfaces. Additionally, the smart charging algorithm was validated in a one-year field test. Experimental results of the field test show elcetronic vehicles (EVs) at six charging stations can be scheduled for charging when the grid connection only allows two EVs to charge concurrently. Runtime measurements demonstrate the smart charging algorithm is applicable in real-time and scales to large fleet sizes.

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