Optimal Control Strategy Design with Minimum Energy Consumption for Connected Vehicle Systems

Author(s):  
Zhuwei Wang ◽  
Yuehui Guo ◽  
Chao Fang ◽  
Meng Li ◽  
Yang Sun ◽  
...  
2011 ◽  
Vol 267 ◽  
pp. 211-216 ◽  
Author(s):  
Peng Zhou ◽  
Hong Ze Xu ◽  
Meng Nan Zhang

Reducing the traction energy consumption plays an important role in railway energy saving. Viewed from the present research situation--the models were all based on the train without energy-feedback, moreover the line condition is the fixed steep down or steep up grades, the train group energy control strategy on continuous change gradient steep downgrades with the energy-feedback is proposed. The advantage for energy-saving of the strategy is proved through the traction calculation in theory. On that basis the optimization method is applied to get the optimal strategy balancing the operation time and energy consumption. By comparing the traditional control strategy with the optimal control strategy, the experiments show that the optimal overall target index of the operation time and energy consumption is much better.


Energy ◽  
2021 ◽  
Vol 228 ◽  
pp. 120631
Author(s):  
Yuanjian Zhang ◽  
Yonggang Liu ◽  
Yanjun Huang ◽  
Zheng Chen ◽  
Guang Li ◽  
...  

2011 ◽  
Vol 20 (6) ◽  
pp. 626-637 ◽  
Author(s):  
Zhongwei Sun ◽  
Shengwei Wang ◽  
Na Zhu

This paper presents a model-based outdoor air flow rate optimal control strategy for multi-zone variable air volume air-conditioning systems with the primary air-handling units. An adaptive optimisation algorithm is adopted for optimising the set point of the outdoor air flow rate to minimise the energy cost, which could compromise the energy consumption of the primary fan and the cooling energy saving by the cold outdoor air. The primary fan energy consumption can be predicted using a simplified incremental fan model and the main parameters of this model are identified online. The cooling energy saving by the outdoor air is estimated online using the enthalpies of the air streams. The lower limit of the outdoor air flow rate is determined by a CO2-based adaptive demand-controlled ventilation strategy using the dynamic multi-space equation to maintain the satisfied indoor air quality (IAQ). Tests were conducted to evaluate the performance of the control strategy applied to a practical building system in simulation environment. The results show that the proposed optimal control strategy can reduce energy consumption significantly, while maintaining a satisfactory IAQ.


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