Logging In-Operation Battery Data from Android Devices: A Possible Path to Sourcing Battery Operation Data

Article Chemistry, Physical

Predicting battery end of life from solar off-grid system field data using machine learning

Antti Aitio et al.

Summary: Using big data techniques, researchers accurately diagnose the health of solar-connected batteries, predicting end of life in advance to address the issue of hundreds of millions lacking access to electricity.

JOULE (2021)

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Article Engineering, Electrical & Electronic

A Novel Consistency Evaluation Method for Series-Connected Battery Systems Based on Real-World Operation Data

Qiushi Wang et al.

Summary: This article presents a cell inconsistency evaluation model for series-connected battery systems based on real-world EV operation data, utilizing consistency indicators and a robust regression method to effectively assess the parameter inconsistency state of the battery system.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2021)

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Review Chemistry, Physical

The challenge and opportunity of battery lifetime prediction from field data

Valentin Sulzer et al.

Summary: Accurate battery life prediction is crucial for various applications, but existing methods based on lab data need to incorporate field data for a complete understanding of cell aging. Challenges arise due to uncontrolled operating conditions, less accurate sensors, and infrequent validation checks in real-world applications. Combining machine learning with physical models shows promise in estimating battery life, assessing second-life condition, and predicting future usage conditions.

JOULE (2021)

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Article Computer Science, Information Systems

Bayesian Network Based State-of-Health Estimation for Battery on Electric Vehicle Application and its Validation Through Real-World Data

Qian Huo et al.

Summary: This paper utilizes Bayesian network to model battery degradation and estimates the State-of-health (SOH) of batteries using Markov Chain Monte Carlo method. The results show that the estimation is very close to the calibrated SOH with a mean absolute error below 4%. The proposed method shows promise for online SOH estimation in real-world EV applications.

IEEE ACCESS (2021)

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Article Chemistry, Physical