As the utilization of lithium-ion batteries in electric vehicles expands, monitoring the usable cell capacity (UCC) is essential for ensuring accurate state-of-health (SOH) estimation. Battery performance degradation is influenced by temperature and constraints. Capacity tests in laboratory settings are typically conducted at low C-rates to approximate equilibrium conditions, whereas in real vehicle applications, charging currents are often much higher. This discrepancy in rates frequently results in deviations between laboratory characterization and on-board Battery Management Systems (BMS) capacity estimation.
To investigate how C-rate of diagnostic Reference Performance Test (RPT) modulates aging effects under temperature and mechanical loading, we conducted long-term cycling tests on lithium iron phosphate/graphite pouch cells at 25°C and 45°C under different constrained conditions. The cycling protocol is a tiered multi-rate protocol. Cells were aged at Block1 under 1C, and UCC evolution was quantified after each block.
The result shows battery aging can be divided into three stages: a decelerated, steady, and accelerated aging stage. The degradation of LFP cells is dominated by loss of lithium inventory (LLI), and elevated temperature accelerates the degradation. By combining differential voltage analysis (DVA), direct current internal resistance, electrochemical impedance spectroscopy, and ultrasonic testing, we found that under 45°C free condition, accelerated aging is consistent with intensified SEI growth and electrolyte decomposition, accompanied by increased LLI, gas-generation, and increased resistance. These signals emerge earlier than the apparent capacity divergence and may serve as early indicators for predicting the onset of rapid degradation. Appropriate constrain mitigates aging, and its influence becomes more pronounced when using higher-rate RPTs.
At 25°C, high-rate RPTs exhibit an apparent capacity recovery. DVA analyses indicate the recovery originates from gradual activation of lithium. Overall, these findings illustrate and explain the degradation characteristics and capacity recovery phenomenon, providing a reference for connecting laboratory standard tests with on-board BMS capacity estimation.