Adaptive iterative learning control of internal temperature for high-speed trains
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12206-023-1238-3.pdf
Reference25 articles.
1. China Ministry of Railways, Railway Statistical Communique in 2022, China Ministry of Railways, China, http://www.china-railway.com.cn.
2. Z. Wang, J. Xu, Y. Wang, L. Wang and R. Wang, Annual energy simulation for the air conditioning of Fuxing high speed trains, Applied Thermal Engineering, 188 (2021) 116591.
3. W. Liu, Q. Deng, W. Huang and R. Liu, Variation in cooling load of a moving air-conditioned train compartment under the effects of ambient conditions and body thermal storage, Applied Thermal Engineering, 31(6–7) (2011) 1150–1162.
4. H. Wang, H. Bi, Y. Zhou and C. Li, Field measurements and numerical analysis of the energy consumption of urban rail vehicle air-conditioning systems, Applied Thermal Engineering, 177 (2020) 115497.
5. J. Zhang, X. Li, T. Zhao and W. Dai, Experimental study on a novel fuzzy control method for static pressure reset based on the maximum damper position feedback, Energy and Buildings, 108 (2015) 215–222.
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