It is important to suppress cavitation phenomenon for lower vibration and noise, which can be realized by structure optimization to reduce cavitation bubbles of flow field. Nonetheless, performance factors in hydrodynamic retarder are usually conflicted when conducting a structure design, it is hard to simultaneously restrain cavitation and improve the retarding performance. In our study, a combination of comprehensive CFD simulation and multi-objective optimization is developed to improve the retarding torque ([Formula: see text]), lessen the volume of Retarder ([Formula: see text]) and reduce the volume of bubbles ([Formula: see text]) in the internal flow field. First, the elaborate CFD simulation calculation, included a refined hexahedral mesh and the stress-blended eddy simulation (SBES), is proposed to investigate the unsteady flow field considering the cavitation, and its accuracy is validated by experimental data. Then, the RSM (Respond Surface Method) approximation model is constructed by combination of DOE (Design of Method) and CFD methods. The NSGA-II (Non-Dominated Sorting Genetic Algorithm) is selected as multi-objective optimization algorithm, and the weight and scale factor of each sub objective are specified. The optimization results, verified by theoretical calculation, show that [Formula: see text] is increased by 22%–24%, [Formula: see text] is reduced by 32%–45% and [Formula: see text] is reduced by 1%. Furthermore, the comparison of the vortex distributions before and after optimization demonstrates that the optimization improves the flow field impact and pressure loss in the retarder and reduces the number of bubbles resulting in the increasing vortex. Additionally, parameters’ effect on the cavitation and the braking performance are analyzed to efficiently achieve the best comprehensive performance of the retarder design. The newly-developed optimization method, which can understand the optimization principle and guide a balance between the cavitation and the retarding performance improvement, will reduce huge trial cost and time cost in the manufacture.
The optimal tracking control of air pressure and air flow is an important guarantee to improve the output characteristics of fuel cells. However, under the load disturbances scenario, the optimal control effect is difficult to guarantee. In order to solve this problem, this paper proposes a new control method based on real-time disturbances observation and MPC optimal control. The decoupling of air pressure and air flow is realized by feedback linearization, and then an extended state observer is designed to achieve accurate estimation of load disturbances. Based on the principle of optimal output power of the fuel cell system, the reference trajectory of air pressure and air flow is obtained. Based on this, the optimal MPC controller is designed to achieve accurate tracking of air pressure and air flow by controlling the motor voltage of the air compressor and the opening of the back pressure valve. Under load disturbances, compared with feedback linearization control, improved tracking and robust performances of the proposed strategy can be exhibited through offline and online tests, the net power of PEMFCs is increased by 3%.
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