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An optimal capacity-constrained fast charging network for battery electric trucks in Germany

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  • Speth, Daniel
  • Plötz, Patrick
  • Wietschel, Martin

Abstract

Battery electric trucks (BET) reduce greenhouse gas emissions in the transport sector but require public charging infrastructure. Truck fast charging networks have been planned in various studies and countries. However, existing charging infrastructure optimization studies ignore relevant actual constraints, such as the size of parking areas or available grid power, leading to unrealistic results. Here, we derive a minimal public fast charging network for BET in Germany with actual real-world capacity limitations. We add capacity constraints to a flow refueling location model (FRLM) which makes the optimization more challenging as it is no longer sufficient to ensure that every path can be travelled but it must be determined which vehicle uses which charging location. The constraint is implemented as hourly maximum number of vehicles that can be served at each location and obtained via queuing theory from local traffic flows. We apply the model to 236,000 origin–destination traffic flows. For 300 km BET range, we identify 124 optimal charging locations. For 15 % BET in stock, e.g. by 2030, this would require 2 to 30 charging points per location with an average of 16 charging points using 17 % of the available truck parking lots per location. Our findings provide input for governments and public charging infrastructure planners. These results indicate that well positioned large initial charging locations can already cover significant shares of BET traffic.

Suggested Citation

  • Speth, Daniel & Plötz, Patrick & Wietschel, Martin, 2025. "An optimal capacity-constrained fast charging network for battery electric trucks in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:transa:v:193:y:2025:i:c:s0965856425000114
    DOI: 10.1016/j.tra.2025.104383
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    References listed on IDEAS

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