Designing Safe Charging Algorithms for Lithium Batteries in Embedded Systems

In the age of smart devices and ubiquitous IoT, lithium-ion batteries have become a staple power source for embedded systems. From fitness trackers to industrial sensors, these compact energy units make untethered operation possible. But with great convenience comes great responsibility—especially when it comes to charging.

Designing a safe and efficient charging algorithm isn’t just about faster charge times. It’s about preventing battery degradation, ensuring user safety, extending product life, and meeting certification requirements. In this article, we’ll explore what developers and embedded engineers need to know about building safe charging algorithms for lithium batteries.

Why Charging Lithium Batteries is Risky

Lithium-ion batteries are sensitive electrochemical devices. Improper charging can lead to:

• Overcharging, which increases the risk of thermal runaway (i.e., fire or explosion)
• Undervoltage issues that degrade the cell's capacity
• Overheating due to rapid current flow or poor thermal management
• Accelerated aging from excessive full charge cycles

Because embedded systems often operate unattended (e.g., remote sensors, wearables), safe charging protocols must be built into the system at the firmware level, not left to chance.

Core Principles of Safe Charging

A safe charging algorithm typically includes the following key phases:

Pre-Charge (Trickle Charge)
If the battery voltage is below a minimum threshold (usually ~3.0V), a small current (~0.1C) is applied to revive the battery gently. This prevents current surges and protects deeply discharged cells.

Constant Current (CC) Phase
The charger applies a constant current (e.g., 0.5C to 1C) until the battery voltage rises to the target charging voltage (usually 4.2V per cell). This is the fastest part of the charging process.

Constant Voltage (CV) Phase
Once the target voltage is reached, the charger holds this voltage constant while the current gradually tapers down. Charging is terminated when current drops below a set threshold (typically ~0.05C).

Termination
Charging should stop when the current falls below the minimum charging current or after a timeout. Continuous trickle charging is not recommended for lithium-ion batteries.

Temperature Monitoring
Throughout the process, the algorithm must monitor battery temperature using thermistors or integrated sensors. Charging is typically suspended if the battery is outside the 0°C–45°C safe zone.

Implementing the Algorithm in Embedded Firmware

Here’s what a typical embedded implementation involves:

• ADC Sampling: Periodically measure voltage, current, and temperature.
• State Machine: Implement a charging state machine with transitions for pre-charge, CC, CV, and termination.
• Timers and Timeouts: Use watchdogs and timers to catch errors or stalled states.
• Safety Cutoffs: Include software-defined upper/lower bounds for voltage, temperature, and current.
• Communication Interface: For smart batteries, communicate with battery management ICs via I2C, SMBus, or CAN.

Here’s a simplified pseudocode example of a charging state machine:

if battery_voltage < 3.0V:
    state = PRECHARGE
elif battery_voltage < 4.2V:
    state = CONSTANT_CURRENT
else:
    state = CONSTANT_VOLTAGE

if current < 0.05C and voltage >= 4.2V:
    state = CHARGE_COMPLETE

Choosing the Right Charge Controller

Depending on your system’s complexity, you can implement charging algorithms in:

• MCU Firmware: Full custom control; ideal for sophisticated embedded designs.
• Battery Management ICs: Off-the-shelf chips like TI’s BQ series or Microchip’s MCP73871 handle most of the logic.
• Hybrid Approach: Use hardware safety features from ICs, but control timing, thresholds, and monitoring from firmware.

Whichever path you choose, always follow the battery cell manufacturer’s specifications for charging parameters.

Design Tips for Robustness and Safety

• Fail-Safe Defaults: Set conservative limits for current, voltage, and temperature in firmware.
• Redundant Monitoring: Use separate ADC channels or watchdogs to double-check key parameters.
• Data Logging: Track charge cycles, temperature extremes, and charge rates to detect aging or failure patterns.
• Cell Balancing: In multi-cell packs, include passive or active balancing to equalize charge and prevent mismatch.
• Real-World Use Case: Low-Power Sensor Node

Imagine a solar-powered environmental sensor with a 1200 mAh lithium-ion battery. The firmware must:

• Wake up periodically to check solar input
• Charge the battery at 0.5C when solar power is sufficient
• Suspend charging when ambient temperature drops below 0°C
• Enter low-power mode when battery is below 10%
• Log charging current and temperature to flash memory

This requires a tight integration of the charging algorithm with power management and sensor control logic—demonstrating how deeply embedded battery safety is in real-world design.

Conclusion

Designing a safe charging algorithm for lithium-ion batteries in embedded systems is not just a technical requirement—it’s a critical design responsibility. Poor charging practices can lead to safety risks, reduced product life, and customer dissatisfaction.

By understanding the chemistry, embracing structured firmware design, and choosing the right hardware, developers can create reliable, long-lasting, and safe embedded systems powered by lithium batteries.

Battery safety is more than compliance—it's part of delivering quality.