Safety-Constrained Energy-Efficient Control for High-Speed Trains Considering Wheel–Rail Interaction

During train operation, the adhesion characteristics between the wheels and rails, which are influenced by driving environments and operating conditions, result in a traction force lower than the motor’s nominal output. Traditional control strategies often overlook the nonlinear relationship between wheel–rail adhesion limits and traction motor output, which can lead to wheel slippage, accelerated wear, and excessive energy consumption. This paper establishes an energy-efficient train control model considering wheel–rail adhesion characteristics. Based on convex optimization methods, the model jointly optimizes the train’s speed trajectory and motor control strategy. Before optimization, nonlinear constraints are simplified through function approximation and tightened McCormick envelope relaxation, significantly reducing the computational complexity of the model. Numerical experiments demonstrate that the proposed driving strategy can adjust the train’s speed in response to poor rail conditions, ensuring adherence to adhesion safety limits. Simulations based on real-world high-speed rail line data in China show that, compared to the traditional EETC model with anti-skid control measures, the proposed model achieves a safer driving strategy. Additionally, in the context of speed trajectory tracking control, it reduces energy consumption by 19.49% compared to the traditional EETC model with anti-skid control measures. Furthermore, the model demonstrates high computational efficiency, indicating its potential for integration into a real-time driving strategy optimization framework.