TY - JOUR
T1 - Modeling memoryless degradation under variable stress
AU - Thomas, Edward V.
AU - Bloom, Ira
AU - Christophersen, Jon P.
AU - Robertson, David C.
AU - Walker, Lee K.
AU - Ho, Chinh D.
AU - Battaglia, Vincent S.
N1 - Publisher Copyright:
© 2019 American Society for Quality.
PY - 2019/7/3
Y1 - 2019/7/3
N2 - Accelerated degradation tests can be used as the basis for predicting the performance or state of health of products and materials at use conditions over time. Measurements acquired at accelerated levels of stress are used to develop models that relate to the degradation of one or more performance measures. Frequently, products/materials of interest are subjected to variable stress levels during their lifetimes. However, testing is usually performed only at a few fixed stress levels. In such cases, cumulative degradation models are developed and assessed by using data acquired under those fixed stress conditions. The degradation rate at any stress condition within the range of the model can be estimated by the derivative of the cumulative model at that stress condition. It follows that, to predict cumulative degradation over variable use conditions, one might integrate the fluctuating degradation rate over time. Existing approaches for doing this consider degradation rates that depend only on the current stress level. Here, we propose to allow the degradation rate to also depend on the current state of health as indicated by the associated performance measure(s). The resulting modeling approach is capable of portraying a broader range of degradation behavior than existing approaches. The assertion of memoryless degradation by using this or any other approach should be assessed experimentally with data acquired under variable stress in order to increase confidence that the integrated rate model is accurate. In this article, we demonstrate the additional capability of the proposed approach by developing empirical memoryless rate-based degradation models to predict resistance increase and capacity decrease in lithium-ion cells that are being evaluated for use in electric vehicles. We then assess the plausibility of these models.
AB - Accelerated degradation tests can be used as the basis for predicting the performance or state of health of products and materials at use conditions over time. Measurements acquired at accelerated levels of stress are used to develop models that relate to the degradation of one or more performance measures. Frequently, products/materials of interest are subjected to variable stress levels during their lifetimes. However, testing is usually performed only at a few fixed stress levels. In such cases, cumulative degradation models are developed and assessed by using data acquired under those fixed stress conditions. The degradation rate at any stress condition within the range of the model can be estimated by the derivative of the cumulative model at that stress condition. It follows that, to predict cumulative degradation over variable use conditions, one might integrate the fluctuating degradation rate over time. Existing approaches for doing this consider degradation rates that depend only on the current stress level. Here, we propose to allow the degradation rate to also depend on the current state of health as indicated by the associated performance measure(s). The resulting modeling approach is capable of portraying a broader range of degradation behavior than existing approaches. The assertion of memoryless degradation by using this or any other approach should be assessed experimentally with data acquired under variable stress in order to increase confidence that the integrated rate model is accurate. In this article, we demonstrate the additional capability of the proposed approach by developing empirical memoryless rate-based degradation models to predict resistance increase and capacity decrease in lithium-ion cells that are being evaluated for use in electric vehicles. We then assess the plausibility of these models.
KW - accelerated testing
KW - calendar aging
KW - lithium-ion batteries
KW - nonisothermal stress
KW - parametric bootstrap
UR - http://www.scopus.com/inward/record.url?scp=85068111747&partnerID=8YFLogxK
U2 - 10.1080/00224065.2019.1569963
DO - 10.1080/00224065.2019.1569963
M3 - Article
AN - SCOPUS:85068111747
SN - 0022-4065
VL - 51
SP - 284
EP - 299
JO - Journal of Quality Technology
JF - Journal of Quality Technology
IS - 3
ER -