Optimization and validation of traction performance for an eight-axle heavy-haul locomotive during gradient starting

To validate the traction performance of two newly developed eight-axle heavy-haul electric locomotives prior to their formal commissioning, a restart test was carried out. The test required each locomotive to individually initiate movement of a 4,700-ton freight train on a track with a 13 promille gradient. During the initial trial, Type B locomotive experienced traction failure, underscoring the need for prompt resolution of its traction deficit. The systematic resolution of this issue involved three key steps. First, a co-simulation framework tailored for Type B was constructed, integrating multibody dynamics and adhesion control models, and the framework was verified by experimental data to ensure reliability. Second, based on the validated framework, optimized solutions were developed—including improved electrical compensation parameters and a novel adhesion control strategy based on the Unscented Kalman Filter (UKF). Simulation results showed that this optimized control scheme increased the overall traction performance of Type B by approximately 10% under low constant-speed conditions. Third, to further reduce starting resistance, driver operating procedures were refined through in-depth resistance analysis. Following the comprehensive optimization of both the control strategy and operating protocols, Type B locomotive successfully passed the gradient restart test. This study delivers a practical, model-driven solution for maximizing traction utilization, offering a critical reference for heavy-haul locomotive engineering.