Ageing in Commercial Li-ion Batteries: Lifetime Testing and Modelling for Electrified Vehicle Applications
Doctoral thesis, 2019
In this thesis, ageing in a commercial pouch cell for vehicle application is investigated through lifetime testing and modelling. The lifetime tests investigate the impact of temperature, current, depth of discharge (DOD) and state of charge (SOC).
Results from lifetime tests are used in the development of an empirical ageing model, to study the ageing as a result of different user cases in a vehicle application. The results showed that the battery lifetime in a vehicle application could be prolonged, without interfering with the driving itself, by better planning of the charging.
Lifetime test results and ageing analysis of the tested cells are used as guidance for the development of a physics-based ageing model. The model includes capacity loss and resistance increase due to resistive film formation and loss of active material.
The lifetime test results showed that for the studied cell, staying below 40% SOC level will improve the lifetime considerably. This was seen in both the calendar ageing tests and the cycling ageing tests. The lifetime tests performed in small SOC intervals at different SOC levels showed that the ageing is separated into two groups, with more pronounced ageing at high SOC and less ageing at low SOC.
The main ageing contribution is the growth of Solid Electrolyte Interphase (SEI), which is also the case seen in the model when using parameters for the SEI growth extracted from calendar ageing data. The more pronounced ageing at higher SOC levels can partly be explained by the SEI growth that is increased at higher SOC level and partly from the contribution of manganese dissolution. This was confirmed by Post Mortem (PM) analysis and successfully captured by the model.
Results from lifetime tests are used in the development of an empirical ageing model, to study the ageing as a result of different user cases in a vehicle application. The results showed that the battery lifetime in a vehicle application could be prolonged, without interfering with the driving itself, by better planning of the charging.
Lifetime test results and ageing analysis of the tested cells are used as guidance for the development of a physics-based ageing model. The model includes capacity loss and resistance increase due to resistive film formation and loss of active material.
The lifetime test results showed that for the studied cell, staying below 40% SOC level will improve the lifetime considerably. This was seen in both the calendar ageing tests and the cycling ageing tests. The lifetime tests performed in small SOC intervals at different SOC levels showed that the ageing is separated into two groups, with more pronounced ageing at high SOC and less ageing at low SOC.
The main ageing contribution is the growth of Solid Electrolyte Interphase (SEI), which is also the case seen in the model when using parameters for the SEI growth extracted from calendar ageing data. The more pronounced ageing at higher SOC levels can partly be explained by the SEI growth that is increased at higher SOC level and partly from the contribution of manganese dissolution. This was confirmed by Post Mortem (PM) analysis and successfully captured by the model.
Battery lifetime tests
Physics-based modelling
Plug-in Hybrid Electric Vehicle (PHEV)
Empiric model
Calendar ageing
KC, Kemigården 4
Opponent: Dr. Daniel Abraham, Argonne National Laboratory, USA
Author
Evelina Wikner
Chalmers, Electrical Engineering, Electric Power Engineering
Electrified vehicles, both pure electric and hybrid, are becoming increasingly popular. Most of the electrified vehicles are using a lithium ion battery (LiB) as energy source. Although the battery price is decreasing it is still a very expensive component, which makes it important that the lifetime of the battery is sufficiently long. In my thesis I’m trying to answer what causes the battery to age and how we can use the battery smarter and prolong the lifetime by taking into account all aspects from the usage in a vehicle down to what happens in the battery and its materials. The project was carried out in collaboration with Uppsala University, Volvo Car Corporation, and ABB, and was funded by the Swedish Energy Agency with some support from the Swedish Electromobility Centre.
In the experimental testing we could observe the anticipated ageing behaviour, where the LiB is ageing faster at higher temperatures, at higher State of Charge (SOC) levels, and when charged/discharged with larger currents. For some type of LiBs low SOC can also accelerate ageing, however, that is not true for the LiB studied here. In particular, when only a small part of the battery energy was used (10% SOC intervals) the lifetime was substantially improved when keeping SOC below 50%.
The experimental results were used to develop a model where different user perspectives of electrified vehicle were taken into account. For a personal vehicle application, the car is parked a substantial amount of its lifetime. The model showed that by planning the charging, and maintaining a low charge level during parking, the battery lifetime could be significantly prolonged. By also charging the battery only as much as needed for the drive, the lifetime could be further improved. These changes are something the driver of an electrified vehicle easily can adapt to improve the battery lifetime.
The project also took a deep dive into the material level ageing of the LiB by opening and analysing the materials of tested cells at Uppsala University. Based on the results, I studied more in detail what triggers the different ageing mechanisms observed. This was done through a physics-based model describing the electrochemical processes. Here we could see that the resistance increase came from the negative electrode material, while the capacity loss came from trapping of Li-ions, and loss of active material in the positive electrode.
In the experimental testing we could observe the anticipated ageing behaviour, where the LiB is ageing faster at higher temperatures, at higher State of Charge (SOC) levels, and when charged/discharged with larger currents. For some type of LiBs low SOC can also accelerate ageing, however, that is not true for the LiB studied here. In particular, when only a small part of the battery energy was used (10% SOC intervals) the lifetime was substantially improved when keeping SOC below 50%.
The experimental results were used to develop a model where different user perspectives of electrified vehicle were taken into account. For a personal vehicle application, the car is parked a substantial amount of its lifetime. The model showed that by planning the charging, and maintaining a low charge level during parking, the battery lifetime could be significantly prolonged. By also charging the battery only as much as needed for the drive, the lifetime could be further improved. These changes are something the driver of an electrified vehicle easily can adapt to improve the battery lifetime.
The project also took a deep dive into the material level ageing of the LiB by opening and analysing the materials of tested cells at Uppsala University. Based on the results, I studied more in detail what triggers the different ageing mechanisms observed. This was done through a physics-based model describing the electrochemical processes. Here we could see that the resistance increase came from the negative electrode material, while the capacity loss came from trapping of Li-ions, and loss of active material in the positive electrode.
Ageing mechanisms & how to prolong battery life in vehicle and energy storage applications’
Volvo Cars (4150395483), 2016-11-09 -- 2016-11-30.
Ageing mechanisms and how to prolong the battery life in vehicle and energy storage applications
Swedish Energy Agency (37725-1), 2014-04-01 -- 2017-06-30.
Subject Categories
Other Chemical Engineering
Electrical Engineering, Electronic Engineering, Information Engineering
ISBN
978-91-7905-166-2
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4633
Publisher
Chalmers
KC, Kemigården 4
Opponent: Dr. Daniel Abraham, Argonne National Laboratory, USA