Download Automotive Air Conditioning: Optimization, Control and by Quansheng Zhang, Shengbo Eben Li, Kun Deng PDF

By Quansheng Zhang, Shengbo Eben Li, Kun Deng

This booklet offers learn advances in car AC structures utilizing an interdisciplinary process combining either thermal technology, and car engineering. It covers a number of issues, resembling: keep an eye on ideas, optimization algorithms, and prognosis schemes built for whilst car air situation structures have interaction with powertrain dynamics. unlike the speedy advances within the fields of establishing HVAC and automobile individually, an interdisciplinary exam of either components has lengthy been overlooked. The content material awarded during this publication not just unearths possibilities while interplay among on-board HVAC and powertrain is taken into account, but additionally offers new findings to accomplish functionality development utilizing model-based methodologies.

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Extra info for Automotive Air Conditioning: Optimization, Control and Diagnosis

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One can observe that the temperature cycles between fixed boundaries. The exact behavior of these cycles relates to the on/off strategy of the compressor clutch. The compressor clutch strategy, however, is not investigated in this work. Nonetheless, a higher ambient temperature results in a higher load for the AC system and the cycle frequency goes up. 10 also reveals that the AC model, in particular Eq. 11), is able to predict the temperature downstream the evaporator. 5 ı C. There should be noted that the accuracy of Tw highly depends on the accuracy of the cooling input PAC_cool .

1), and the outside temperature is denoted as TnC1 . m C 1/th node in the reduced-order model and we denote its temperature as TN mC1 . m C 1/th super-node. T; U; Q/=CN k . k/ N k. T s U PN . //=CN . / e k . 29) where X N k . / WD U i2 X PN . k/ i2 P i; Q X e k . t/ denotes the outside temperature. 32) described later. N / and Since U and Q are external inputs to the full-order model, we can also take U. P N Q. 30) as the super-inputs to the reduced-order model. 30) depends on T, which is the state vector of the is that the term W.

In the following, a compact state-space representation is presented for building thermal dynamics. To establish a Markov chain analogy in the next section, the outside temperature is also taken as a “virtual state” TnC1 to the building system. We assign a very large “virtual capacitance” to the outside node: CnC1 Ci , for i D 1; : : : ; n. Letting CnC1 ! 1) where the state vector T WD ŒT1 ; : : : ; TnC1 T , the control vector U WD T T P P P Œm P in P in 1 ;:::;m N ; 0; : : : ; 0 , and the heat gain vector Q WD ŒQ1 ; : : : ; QN ; 0; : : : ; 0 .

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