Author
Listed:
- Ren, Yuankai
- Lu, Hangyu
- Zhang, Ning
- Wu, Xiaodong
Abstract
The cooling fan constitutes a primary source of vibration and noise in automotive thermal management systems (TMS), particularly critical for new energy vehicles (NEVs), where its performance directly impacts overall noise, vibration, and harshness (NVH). However, the coordinated control of thermal system response and fan vibration cost has rarely been addressed, primarily due to the challenging trade-off between temperature regulation and structural vibration suppression. This study proposes a data-assisted hybrid modeling approach for cooling fans system, which integrates experimental data and virtual prototyping data to identify theoretical model parameters and determine boundary conditions. By combining these data sources with theoretical models, the proposed method significantly improves computational efficiency for iterative calculations compared to conventional finite element methods (FEM), while experimental validation confirms the model’s accuracy and reliability. For the TMS featuring fan-assisted auxiliary water-cooling, a dual-loop strategy based on nonlinear model predictive control (NMPC) was developed, which first selects an appropriate proportional valve opening based on the current temperature and fan vibration-speed relationship, then determines the optimal rotational speed via NMPC to achieve simultaneous temperature regulation and vibration suppression. Simulation-based verification demonstrates that the proposed control architecture enables rapid temperature stabilization while preventing prolonged high-amplitude fan operation. Through experimental and simulation validation, the proposed modeling approach of the fan system demonstrates nearly 80-fold improvement in computational efficiency compared to conventional finite element methods. Moreover, the developed control strategy effectively prevents excessive steady-state vibration amplitudes of the fan.
Suggested Citation
Ren, Yuankai & Lu, Hangyu & Zhang, Ning & Wu, Xiaodong, 2025.
"Towards the optimal leverage of dynamic performance and vibrational cost: A novel nonlinear control strategy for thermal management in the fuel-cell system,"
Energy, Elsevier, vol. 335(C).
Handle:
RePEc:eee:energy:v:335:y:2025:i:c:s0360544225037831
DOI: 10.1016/j.energy.2025.138141
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