Residual and stratified branching particle filters

Kouritzin, Michael A.

doi:10.1016/j.csda.2017.02.003

Cited by 14 publications

(27 citation statements)

References 21 publications

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“…To avoid this issue, resampling can be used, in which the basic idea is to reproduce the particles with higher weight while abandoning those with lower. Amongst different resampling strategies [36], the stratified resampling method is efficient and relatively simple with the complexity of O(N s ). The procedure to implement the stratified resampling can be summarized as follows:…”

Section: The Proposed Algorithmmentioning

confidence: 99%

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

et al. 2019

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This paper develops a new prediction method for the aging trajectory of lithium-ion batteries with significantly reduced experimental tests. This method is driven by data collected from two types of battery operation modes. The first type is accelerated aging tests that are performed under stress factors, such as overcharging, over-discharging and large current rates, and cover most of the battery lifespan. In the second operation mode, the same kinds of cells are aged at normal speeds to generate a partial aging profile. An accelerated aging model is developed based on the first type of data and is then migrated as a new model to describe the normalspeed aging behavior. Under the framework of Bayesian Monte Carlo algorithms, the new model is parameterized based on the second type of data and is used for prediction of the remaining battery aging trajectory. The proposed prediction method is validated on three types of commercial batteries and also compared with two benchmark algorithms. The sensitivity of results to the number of cycles is investigated for both modes. Illustrative results demonstrate that based on the normal-speed aging data collected in the first 30 cycles, the proposed method can predict the entire aging trajectories (up to 500 cycles) at a root-mean-square error of less than 2.5% for all considered scenarios. When only using the first five-cycle data for model training, such a prediction error is bounded by 5% for aging trajectories of all the tested batteries.

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Section: The Proposed Algorithmmentioning

confidence: 99%

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

et al. 2019

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“…In order to reduce the particle degradation problem, the following three-step resampling technique is adopted [41].…”

Section: Conventional Pf-based Aging Trajectory Predictionmentioning

confidence: 99%

Real-time aging trajectory prediction using a base model-oriented gradient-correction particle filter for Lithium-ion batteries

Tang

Liu

Wang

et al. 2019

Journal of Power Sources

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“…Different branching algorithms are presented in Kouritzin (2017a). The algorithms were originally developed in the context of sequential Monte Carlo methods in Kouritzin (2017c) and analyzed in Kouritzin (2017b). Here, for optimal performance, we use the Effective Particle Branching algorithm, which we present in details in Subroutine A2 in Appendix B.…”

Section: 3mentioning

confidence: 99%

VIX-linked fees for GMWBs via explicit solution simulation methods

Kouritzin

MacKay

2018

Insurance: Mathematics and Economics

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In a market with stochastic volatility and jumps, we consider a VIX-linked fee structure (see Cui et al. (2017)) for variable annuity contracts with guaranteed minimum withdrawal benefits (GMWB). Our goal is to assess the effectiveness of the VIXlinked fee structure in decreasing the sensitivity of the insurer's liability to volatility risk. Since the GMWB payoff is highly path-dependent, it is particularly sensitive to volatility risk, and can also be challenging to price, especially in the presence of the VIX-linked fee. In this paper, following Kouritzin (2018), we present an explicit weak solution for the value of the VA account and use it in Monte Carlo simulations to value the GMWB guarantee. Numerical examples are provided to analyze the impact of the VIX-linked fee on the sensitivity of the liability to changes in market volatility.

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Residual and stratified branching particle filters

Cited by 14 publications

References 21 publications

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

Real-time aging trajectory prediction using a base model-oriented gradient-correction particle filter for Lithium-ion batteries

VIX-linked fees for GMWBs via explicit solution simulation methods

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