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An ultra-high-speed electric air compressor (UHSEAC) generates a load torque component during operation, leading to unstable output. As air passes through the UHSEAC, the air density changes significantly, resulting in increased uneven distribution. This causes rapid changes in gas parameters, making them difficult to extract. Consequently, the behavior of load torque component variations under ultra-high-speed operating conditions (UHSOC) remains unclear. The influence of UHSOC on the load torque component has not been studied. In this article, the fluid model of the UHSEAC is established and verified, and the load torque component is extracted based on this model. The influence of speed and torque on the load torque component under UHSOC is then studied. The results show that the frequency of the load torque component increases by 14.29% as the speed increases from 70,000 rpm to 90,000 rpm. Additionally, as the torque increases from 1.3 Nm to 1.7 Nm, the amplitude of the load torque component increases by 69.56%. These findings provide valuable guidance for future scholars seeking to optimize UHSEAC design to reduce load torque components. [ABSTRACT FROM AUTHOR]

The control strategy of the gas supply subsystem is very important to ensure the performance and stability of the fuel cell system. However, due to the inherent nonlinear characteristics of the fuel cell gas supply subsystem, the traditional control strategy is mainly based on proportional integral (PI) control, which has the disadvantages of large limitation, large error, limited immunity, and inconsistent control performance, which seriously affects its effectiveness. In order to overcome these challenges, this paper proposes an optimal control method for air supply subsystems based on nonlinear active disturbance rejection control (ADRC). Firstly, a seven-order fuel cell system model is established, and then, the nonlinear ADRC and traditional PI control strategies are compared and analyzed. Finally, the two strategies are simulated and compared. The validation results indicate that the integral absolute error (IAE) measure of PI control is 0.502, the integral square error (ISE) measure is 0.1382, and the total variation (TV) measure is 399.1248. Compared with the PI control, the IAE and ISE indexes of ADRC were reduced by 61.31% and 58.03%, respectively. ADRC is superior to PI control strategy in all aspects and realizes the efficient adjustment of the system under different working conditions. ADRC is more suitable for the nonlinear characteristics of the gas supply system and is more suitable for the oxygen excess ratio (OER). [ABSTRACT FROM AUTHOR]

Hydrogen has the physical and chemical characteristics of being flammable, explosive and prone to leakage, and its safety is the main issue faced by the promotion of hydrogen as an energy source. The most common scene in vehicle application is the longitudinal wind generated by driving, and the original position of hydrogen concentration sensors (HCSs) did not consider the influence of longitudinal wind on the hydrogen leakage trajectory. In this paper, the computational fluid dynamics (CFD) software STAR CCM 2021.1 is used to simulate the hydrogen leakage and diffusion trajectories of fuel cell vehicles (FCVs) at five different leakage locations the longitudinal wind speeds of 0 km/h, 37.18 km/h and 114 km/h, and it is concluded that longitudinal wind prolongs the diffusion time of hydrogen to the headspace and reduces the coverage area of hydrogen in the headspace with a decrease of 81.35%. In order to achieve a good detection effect of fuel cell vehicles within the longitudinal wind scene, based on the simulated hydrogen concentration–time matrix, the scene clustering method based on vector similarity evaluation was used to reduce the leakage scene set by 33%. Then, the layout position of HCSs was optimized according to the proposed multi-scene full coverage response time minimization model, and the response time was reduced from 5 s to 1 s. [ABSTRACT FROM AUTHOR]