Consumers, Vehicles and Energy Integration (CVEI) - D3.2. Battery State of Health Model Report

Abstract:

The objective of the Consumers, Vehicles and Energy Integration project is to inform UK Government and European policy and to help shape energy and automotive industry products, propositions and investment strategies. Additionally, it aims to develop an integrated set of analytical tools that models future market scenarios in order to test the impact of future policy, industry and societal choices. The project is made up of two stages:

• Stage 1 aims to characterize market and policy frameworks, business propositions, and the integrated vehicle and energy infrastructure system and technologies best suited to enabling a cost-effective UK energy system for low-carbon vehicles, using the amalgamated analytical toolset.
•  Stage 2 aims to fill knowledge gaps and validate assumptions from Stage 1 through scientifically robust research, including real world trials with privatevehicle consumers and case studies with business fleets. A mainstream consumer uptake trial will be carried out to measure attitudes to PiVs after direct experience of them, and consumer charging trials will measure mainstream consumer PiV charging behaviours and responses to managed harging options

This report represents Deliverable D3.2, Battery State of Health Model. The purpose of this report is to describe the development and validation of an algorithm that quantifies battery ageing based on input parameters that can be either inferred from Electric Vehicle (EV) usage or measured on-board. A battery is assumed to reach its (automotive) end of life when its State of Health (SOH), defined as the ratio of its measured capacity to its capacity when new, decreases to 80%. Example outputs have been generated in order to show how the algorithm can be used to assess the impact ofdifferent levels of integration of EVs into the electricity grid on battery life (and thus vehicle economics). Note that the report does not aim to present a comprehensive analysis of all combinations (which can be carried out by model users), but rather to explain how the algorithm was developed. The work reported in this deliverable forms part of the “Vehicle Energy Management Systems and Technologies” work carried out in Stage 1 of the project. The separate spreadsheet (accompanying this report) provides more detail in the form of the Battery State of Health Model itself. It should be noted that the project team had difficulties delivering the full functionality specified for this deliverable. Consequently, this model provides a relatively high-level overview of battery degradation and state of health, which will be further developed during Stage 2 of the project.

Author(s):

Element Energy