Battery analytics-driven rental-like agreements for lithium-ion batteries
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Insinööritieteiden korkeakoulu |
Master's thesis
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Authors
Date
2022-01-24
Department
Major/Subject
Mcode
Degree programme
Master’s programme in Energy Storage
Language
en
Pages
90
Series
Abstract
Due to the Lithium-Ion battery’s exceptionally desirable parameters such as high energy density and low discharge rate, it has become the most popular and dynamically developing energy storage technology, both for stationary systems and as a source of power in mobile applications. Apart from the high price, one of its main downsides is degradation, which leads to loss of capacity, an increase of internal resistance, and a risk of failure. This process is very complex and strongly dependent on battery operating parameters, such as temperature, voltage, current, State-of-Charge, number, and depth of cycles. The analysis conducted using a semi-empirical, testbench data-based degradation model with e-bus in-field operating data as input shows, that the degradation rate varies significantly even for small changes in working parameters’ values. Cases with usage profiles with parameters higher or lower by 2/5/10/15% compared to mean monthly values were investigated. In extreme cases, the degradation rate was higher by 66% (15% higher parameters) or lower by 37% (15% lower parameters). Moreover, only by aggregating real monthly parameters into mean ones, the resulting degradation rate changed by 20%. In extreme cases, the difference of monthly degradation rate between minimum and maximum values was 46%. Also, the impact of considering battery degradation on revenue in stationary and mobile applications was analyzed. The authors claim that an optimal usage profile that minimizes battery degradation leads to a significant increase in battery life and results in higher revenues or savings. Both calculations and results from the literature, lead to the conclusion that by knowing usage profile one is able to better assess battery degradation, its lifetime and as a result make better decisions. These observations may be used in the battery rental business for stationary or mobile applications. Nowadays, battery analytics are not widely used in the rental business and there is no differentiation between rental prices based on users’ profiles. This may lead to inaccurate financial projections, lack of trust on both sides and result in the battery rental business being not feasible. In this work, the framework of the analytics-driven rental-like agreement was shown, with necessary stakeholders, relations between them, and methodology for conducting such agreement. Battery working parameters are collected to verify the contract and potentially adjust the rental price. Moreover, a simplified method of monthly rent calculation was proposed. Finally, this method was demonstrated in an example.Description
Supervisor
Santasalo-Aarnio, AnnukkaThesis advisor
Morawietz, LutzFriebel, Christoph
Keywords
lithium-ion, battery, degradation, diagnostics, electric vehicle, rental