Freight vehicles represent a most important component of technospheric safety in both production and social spheres of Yakutia, which is part of the permafrost zone of Russia. Trucks are the sole means of cargo transportation capable of maintaining communication links between all settlements during the winter, thus ensuring normal living conditions in the region. Relevant tasks include improving the reliability of trucks, specifically by identifying features in the failure statistics of various parts and systems associated with typical changes in operating conditions in the permafrost. The aim of the study is to establish regularities in the impact of seasonal operating conditions on the operability and reliability of leaf springs in KAMAZ trucks used in the permafrost, based on the analysis of failure time series. Modeling of leaf springs failures time series has been carried out using Fourier series decomposition with the allocation of significant harmonics. A mathematical model was created that satisfactorily approximates the dynamics of failures. The model consists of the mean monthly number of failures and five significant harmonics from the Fourier decomposition. Interrelation between rhythmological features of failures and operating conditions was demonstrated. The novelty of the results lies in the contribution to solving methodological issues concerning the study of reliability of automotive parts taking into account seasonal operational factors and ranking their significance in causing the failures. The proposed method enables improved accuracy of short-term failure forecasts and enhanced effectiveness of vehicle maintenance, adhering to the principles of technosphere safety such as prevention, control, and monitoring.