Battery Calendar: Track Cycle Count and Capacity Fade

A battery calendar tracks cycle count, capacity fade, and usage patterns over the entire lifetime of a battery pack, providing the data needed to predict remaining useful life and schedule replacements. For solar installations, e-bikes, and industrial applications in India where battery replacement costs ₹10,000-50,000+, knowing exactly when a battery will need replacement prevents both premature waste and unexpected failures.

What Is a Battery Calendar?

A battery calendar is a logging system that records every charge/discharge cycle, tracks cumulative throughput, and monitors capacity degradation over months and years. Think of it as a battery’s health diary.

Key data points logged per cycle:

• Date and time of charge start/end
• Charge Wh input and discharge Wh output
• Cycle depth (DoD percentage)
• Average temperature during cycle
• Measured capacity (if full cycle)
• Cumulative cycle count (adjusted for partial cycles)

Key Metrics to Track

1. Equivalent Full Cycles (EFC):
   EFC += depth_of_discharge / 100 per cycle
   A 50% DoD cycle = 0.5 EFC
   A 100% DoD cycle = 1.0 EFC

2. Capacity Fade (%):
   Fade = (Initial_capacity - Current_capacity) / Initial_capacity x 100
   End of life: typically 80% of initial capacity (20% fade)

3. Round-Trip Efficiency:
   Efficiency = Wh_out / Wh_in x 100
   Healthy Li-ion: 95-98%
   Degraded Li-ion: 85-92%
   Declining efficiency indicates growing internal resistance

4. Calendar Age Factor:
   Even unused, batteries degrade ~2-3% per year at 25degC
   In Indian conditions (30-35degC average): ~4-5% per year
   Factor: age_months x monthly_fade_rate

Hardware Setup

Build a battery calendar logger using:

• ESP32: WiFi connectivity for cloud data upload
• INA219: Continuous current and voltage monitoring
• NTC thermistor: Battery temperature tracking
• RTC (DS3231): Accurate timestamps even during power loss
• SD card: Local backup of all data

ESP32 Cloud Logger

// Battery Calendar Logger (ESP32 + INA219)
// Logs to ThingSpeak or Google Sheets every 60 seconds

#include <WiFi.h>
#include <HTTPClient.h>
#include <Adafruit_INA219.h>

Adafruit_INA219 ina;
float cycleWhIn = 0, cycleWhOut = 0;
float totalEFC = 0, initialCapacity = 2200; // mAh
int cycleCount = 0;
bool charging = false;

void logToCloud(float v, float i, float p, float wh, float efc) {
  HTTPClient http;
  String url = "https://api.thingspeak.com/update?api_key=YOUR_KEY";
  url += "&field1=" + String(v, 2);
  url += "&field2=" + String(i, 1);
  url += "&field3=" + String(p, 1);
  url += "&field4=" + String(wh, 1);
  url += "&field5=" + String(efc, 2);
  http.begin(url);
  http.GET();
  http.end();
}

Analysing Capacity Fade

After collecting months of data, you can predict remaining battery life:

Linear fade model (simplest):
  If capacity dropped 5% in 200 EFC
  Rate = 5% / 200 = 0.025% per EFC
  Remaining life to 80%: (100-80-5) / 0.025 = 600 more EFC

  At 1 cycle/day: 600 days = ~20 months remaining

Non-linear model (more accurate):
  Li-ion fade accelerates after ~60% of cycle life
  Plot capacity vs EFC and fit a curve
  Extrapolate to 80% threshold

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FAQ

How often should I run a full capacity test?

Every 50-100 cycles (approximately monthly for daily-cycled batteries). The full capacity test involves a complete charge followed by a controlled discharge to the cutoff voltage, measuring total mAh delivered. This is the most accurate way to track capacity fade.

Does temperature logging really matter for Indian batteries?

Absolutely. Indian ambient temperatures (25-45degC) significantly impact battery ageing. Every 10degC above 25degC roughly doubles the calendar ageing rate. Temperature data helps you correlate seasonal capacity changes and optimise battery placement (shade, ventilation).