No abstract

The interpolation method of discrete spectrum is applied to the engine excitation force identification. The frequency, amplitude, and phase of the vibration response of each measuring point on cylinder surface are obtained accurately based on the interpolation method. Combination with the inertia parameters and the dynamic properties of the mounts, the excitation force, and moment at the center of gravity of engine can be exactly retrieved. The nonlinear problem caused by the imprecise phase of the measurement points is avoided, and the identified method is simplified. Simulation results confirm the importance of the interpolation method on the accurate identification of the excitation force. Influences on the excitation force identification are analyzed quantitatively. The reasons causing the errors are analyzed and the avoidance methods are given too. Through the multi-rigid-body dynamics model simulation, the excitation force identification method is confirmed. Then, the proposed method is carried out on an engine.

Misfiring creates a unique pattern attributed to a particular cylinder. When a misfire occurs, the balance of the engine is destroyed, and the generalized force at the centre of gravity (C.G.) of the engine is changed. In this paper, a new misfire detection method is presented based on the identification of the generalized force at the engine centre of gravity. Based on the engine acceleration signals at the mounts, through the use of the discrete spectrum interpolation method, the accurate amplitudes and phases of the acceleration signals are extracted, and then, the generalized force at the centre of gravity is calculated. Through analysing the main harmonic orders of the generalized force, the misfire features are accurately extracted and classified. Both the simulation examples and test bed results prove the effectiveness of the present method in detecting misfire faults in combustion engines.INDEX TERMS Engine, misfire detection, the centre of gravity, the generalized force.

Aiming at the optimal path and planning efficiency of global path planning for intelligent driving, this paper proposes a global dynamic path planning method based on improved A ∗ algorithm. First, this method improves the heuristic function of the traditional A ∗ algorithm to improve the efficiency of global path planning. Second, this method uses a path optimization strategy to make the global path smoother. Third, this method is combined with the dynamic window method to improve the real-time performance of the dynamic obstacle avoidance of the intelligent vehicle. Finally, the global dynamic path planning method of the proposed improved A ∗ algorithm is verified through simulation experiments and real vehicle tests. In the simulation analysis, compared with the modified A ∗ algorithm and the traditional A ∗ algorithm, the method in this paper shortens the path distance by 2.5%∼3.0%, increases the efficiency by 10.3%∼13.6% and generates a smoother path. In the actual vehicle test, the vehicle can avoid dynamic obstacles in real time. Therefore, the method proposed in this paper can be applied on the intelligent vehicle platform. The path planning efficiency is high, and the dynamic obstacle avoidance is good in real time.

Highly dispersed Cu@FeCo/rGO catalysts have been prepared by two-step reduction method and used for hydrogen production from ammonia borane (NH3BH3, AB) hydrolysis at 298 K.