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On Optimal Battery Sizing for Electric Vehicles

Felix Wieberneit, Emanuele Crisostomi, Anthony Quinn, Homayoun Hamedmoghadam, Pietro Ferraro, Robert Shorten

Abstract

In this paper, we introduce a quantitative framework to optimize electric vehicle (EV) battery capacities, considering two criteria: upfront vehicle cost and charging inconvenience cost. For this purpose, we (1) develop a comprehensive model for charging inconvenience costs, incorporating both charging time and detours, improving on existing studies, (2) show, through extensive simulations and analytical models, how charging inconvenience cost is affected by different battery capacity and charging infrastructure configurations, (3) introduce an optimisation framework to determine optimal battery capacities based on charging inconvenience and vehicle cost, and (4) show that optimal battery capacities can be influenced by strategic investments in charging infrastructure and tax/incentive policies. The proposed framework provides actionable insights into the sustainable design of EV systems, supporting the development of cost-effective and convenient electric mobility solutions.

On Optimal Battery Sizing for Electric Vehicles

Abstract

In this paper, we introduce a quantitative framework to optimize electric vehicle (EV) battery capacities, considering two criteria: upfront vehicle cost and charging inconvenience cost. For this purpose, we (1) develop a comprehensive model for charging inconvenience costs, incorporating both charging time and detours, improving on existing studies, (2) show, through extensive simulations and analytical models, how charging inconvenience cost is affected by different battery capacity and charging infrastructure configurations, (3) introduce an optimisation framework to determine optimal battery capacities based on charging inconvenience and vehicle cost, and (4) show that optimal battery capacities can be influenced by strategic investments in charging infrastructure and tax/incentive policies. The proposed framework provides actionable insights into the sustainable design of EV systems, supporting the development of cost-effective and convenient electric mobility solutions.

Paper Structure

This paper contains 35 sections, 11 equations, 9 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Structure of the Paper
  3. Optimization Framework for EV Battery Capacities
  4. EV Purchase Cost after Subsidies, $c_p$
  5. Charging Inconvenience Cost $c_e$
  6. Analytical Estimation of Charging Inconvenience Time $\tau_e$
  7. Conversion of the Charging Inconvenience Time $\tau_e$ to Inconvenience Cost $c_e$
  8. Estimation of $c_e$ with Urban Mobility Simulations
  9. Simulation Model Overview
  10. Road Network:
  11. Charging Infrastructure:
  12. Mobility Demand:
  13. EV specifications:
  14. Charging Logic:
  15. Data Collection and Inconvenience Estimation:
  16. ...and 20 more sections

Figures (9)

  • Figure 1: Regression analysis of $c_{p,base}$ as a function of $B$.
  • Figure 2: Sensitivity of charging inconvenience time $\tau_e$ with respect to its parameters.
  • Figure 3: Overview of the main components of the simulation tool used to measure EV charging inconvenience.
  • Figure 4: (a) and (b) present results for the simulated E-Mobility Scenarios 1 and 2 respectively.
  • Figure 5: Charging infrastructure placement strategies A (distributed charging infrastructure) and B (concentrated charging infrastructure in a single peripheral point).
  • ...and 4 more figures