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The centrifugal compressor is one of the most commonly used air compressors for fuel cell air supply systems, and it has the small volume, high pressure ratio and low noise. However, surge in a centrifugal compressor severely limits its stable flow range. In this paper, a mathematical model of the compressor aerodynamic performance based on the energy transfer method was established, some parameters of model were identified by experimental data, and the model was validated through experiments. Then the dynamic model of the compression system was derived based on the compressor model and the Moore-Greitzer model. The stability analysis of the compression system was conducted, and it was strictly proved that when the compression system is unstable, there is the limit cycle in this nonlinear system, namely the surge cycle. Furthermore, the simulation of the compression system was conducted and the instability condition of the compression system was presented.

Tire forces and moments play an important role in vehicle dynamics and safety. X-by-wire chassis components including active suspension, electronic powered steering, by-wire braking, etc can take the tire forces as inputs to improve vehicle’s dynamic performance. In order to measure the accurate dynamic wheel load, most of the researches focused on the kinematic parameters such as body longitudinal and lateral acceleration, load transfer and etc. In this paper, the authors focus on the suspension system, avoiding the dependence on accurate mass and aerodynamics model of the whole vehicle. The geometry of the suspension is equated by the spatial parallel mechanism model (RSSR model), which improves the calculation speed while ensuring the accuracy. A suspension force observer is created, which contains parameters including spring damper compression length, push rod force, knuckle accelerations, etc., combing the kinematic and dynamic characteristic of the vehicle.

This paper focuses on lane-changing trajectory planning and trajectory tracking control in autonomous vehicle technology. Aiming at the lane-changing behavior of autonomous vehicles, this paper proposes a new lane-changing trajectory planning method based on particle swarm optimization (PSO) improved third-order Bezier curve path planning and polynomial curve speed planning. The position of Bezier curve control points is optimized by the particle swarm optimization algorithm, and the lane-changing trajectory is optimized to improve the comfort of lane changing process. Under the constraints of no-collision and vehicle dynamics, the proposed method can ensure that the optimal lane-changing trajectory can be found in different lane-changing scenarios. To verify the feasibility of the above planning algorithm, this paper designs the lateral and longitudinal controllers for trajectory tracking control based on the vehicle dynamic tracking error model.