Relevance. Currently, global warming represents one of the most pressing environmental challenges, requiring immediate action. One of the key strategies for mitigating anthropogenic impact on the climate is the transition to renewable energy sources. However, their intermittent nature (dependence on sunlight, wind, and other factors) necessitates the use of efficient energy storage systems. Moreover, in resource exploitation, energy storage systems may be required as an auxiliary source of electrical energy in critical situations. In this context, lithium-ion batteries have gained particular importance as efficient energy storage devices due to a number of inherent advantages. However, the widespread deployment of lithium-ion batteries is hindered by a critical safety issue – thermal runaway. Therefore, thermal state monitoring of lithium-ion batteries plays a crucial role in ensuring safe operation and extending service life. Aim. To develop an algorithm for estimating the internal electrochemical temperature of lithium-ion batteries based on external sensors mounted on the battery surface. Methods. The experimental data were collected and analyzed using mathematical and numerical methods for parameter calculation. Results and conclusions. The study demonstrates that during charging, the maximum absolute estimation error does not exceed 0.85°C, while during discharging it remains below 3.1°C. The obtained results indicate that the proposed algorithm provides sufficiently accurate estimation of internal lithium-ion battery temperature based on surface temperature and voltage measurements.