Abstract This study presents a method for determining the optimal gear ratio in electric trains by examining the effects of motor efficiency, wheel wear, and relative damage to the input and output shafts of the reduction gear. In electric trains, reduction gears and wheels are critical for converting the driving motor’s torque and determining the motor’s operational point, which in turn affects efficiency and durability. Over time, wheel wear from regular use and periodic profiling reduces the wheel radius, causing an effective increase in the gear ratio, which impacts the motor efficiency and load distribution across drivetrain components. This study models the dynamic behavior of the vehicle’s drivetrain system using MATLAB/Simulink and incorporates real-world data on wheel wear to address the problem. Through simulations with varying gear ratios, it analyzes changes in motor efficiency and uses Miner’s rule to assess the relative damage on the reduction gear’s input and output shafts. The results enable the identification of a gear ratio that balances motor efficiency and reduces cumulative fatigue damage, which is especially important for maintaining long-term drivetrain durability. This approach provides a systematic way to enhance the overall performance and lifespan of electric train systems by selecting a gear ratio that optimally aligns efficiency and durability. Keywords: miner’s rule; revolution counting method; motor efficiency; gear ratio; quantified damage; longitudinal train dynamics; pareto optimal point; utopia point; Euclidian distance