Battery Health Management

Forecast battery health status changes and remaining useful life trends from charge/discharge time-series data.

Overview

In both EV and electrochemical energy storage scenarios, batteries are the most critical and expensive assets. State of Health (SOH) and Remaining Useful Life (RUL) cannot be measured directly and exhibit complex changes driven by temperature, C-rate, depth of discharge, and calendar aging. TimechoAI models degradation trends from charge/discharge process data and long-term operating conditions, helping teams identify abnormal degradation and high-risk cells earlier.

Key value

Identify long-term battery degradation trends
Detect abnormal degradation and weak cells early
Support SOH / RUL assessment
Assist O&M and charge/discharge strategy optimization

Typical applications

Cell health trend analysis

Continuously track the health status of individual cells or modules.

Identify degradation differences across cells
Observe long-term aging rate changes
Support batch health assessment

High-risk battery alerts

Detect abnormal heating, abnormal degradation, or potential high-risk objects early.

Help locate weak cells
Support focused inspections and reviews
Reduce risk of failure escalation

Charge/discharge boundary optimization

Optimize operating strategies based on real degradation trends.

Adjust C-rates and charge/discharge windows
Balance performance and longevity goals
Support long-term ROI optimization of storage assets

Key inputs

Voltage and current curves during charge/discharge
Cell temperature, heating rate, and temperature distribution
SOC / DOD change sequences
Cycle count and calendar aging time
Internal resistance estimates and operating condition labels

Outputs

SOH change trend
RUL estimate
Abnormal degradation or high-risk object alerts
Analysis results to support O&M decisions and strategy adjustments

Use Timer to identify degradation trends and support proactive O&M for storage and EV battery scenarios. See integration →