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Article
Publication date: 11 October 2019

Wei Qin, Huichun Lv, Chengliang Liu, Datta Nirmalya and Peyman Jahanshahi

With the promotion of lithium-ion battery, it is more and more important to ensure the safety usage of the battery. The purpose of this paper is to analyze the battery operation…

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Abstract

Purpose

With the promotion of lithium-ion battery, it is more and more important to ensure the safety usage of the battery. The purpose of this paper is to analyze the battery operation data and estimate the remaining life of the battery, and provide effective information to the user to avoid the risk of battery accidents.

Design/methodology/approach

The particle filter (PF) algorithm is taken as the core, and the double-exponential model is used as the state equation and the artificial neural network is used as the observation equation. After the importance resampling process, the battery degradation curve is obtained after getting the posterior parameter, and then the system could estimate remaining useful life (RUL).

Findings

Experiments were carried out by using the public data set. The results show that the Bayesian-based posterior estimation model has a good predictive effect and fits the degradation curve of the battery well, and the prediction accuracy will increase gradually as the cycle increases.

Originality/value

This paper combines the advantages of the data-driven method and PF algorithm. The proposed method has good prediction accuracy and has an uncertain expression on the RUL of the battery. Besides, the method proposed is relatively easy to implement in the battery management system, which has high practical value and can effectively avoid battery using risk for driver safety.

Details

Industrial Management & Data Systems, vol. 120 no. 2
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 7 February 2024

Saeideh Moosavi, Mehran Ghalenoei, Aisa Maleki and Rohollah Kalhor

This study aims to investigate the effect of the Diamond Justice model on self-efficiency with the mediating role of job stress among the staff of Qazvin hospitals affiliated with…

59

Abstract

Purpose

This study aims to investigate the effect of the Diamond Justice model on self-efficiency with the mediating role of job stress among the staff of Qazvin hospitals affiliated with Qazvin University of Medical Sciences. This study is a cross-sectional descriptive-analytical study conducted among the staff of Qazvin hospitals affiliated with Qazvin University of Medical Sciences in 2020.

Design/methodology/approach

Sampling was performed using the structural equation method. Data collection tools included three sections: demographic information, justice and self-efficiency questionnaire and job stress questionnaire. Data were finally analyzed using SPSS software version 26 and AMOS version 23 at a significance level of 0.05.

Findings

The structural equation model’s standard estimation coefficients show that all existing paths are at a significant level. Finally, the regression analysis showed that justice is inversely related to stress level (ß = −0.185, p = 0.015). Justice is directly related with self-efficiency (ß = 0.282, p < 0.001).

Originality/value

Justice, stress and self-efficacy have been measured in various studies among health workers. However, a fitting model showing these three variables’ interaction was necessary. Therefore, this study tries to conceptualize the multifaceted relationships of the components of these concepts by presenting a model.

Details

International Journal of Human Rights in Healthcare, vol. 17 no. 5
Type: Research Article
ISSN: 2056-4902

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