4.7 Article

Simultaneous optimization of urea dosing and ammonia coverage ratio of selective catalytic reduction system in diesel engine by using physico-chemical model based NSGA-II algorithm

期刊

APPLIED THERMAL ENGINEERING
卷 154, 期 -, 页码 46-62

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2019.03.031

关键词

Selective catalytic reduction system; Urea dosing and ammonia coverage ratio; Optimization; Non-dominated sorting genetic algorithm (NSGA-II); Diesel emissions control

资金

  1. National key R&D Program of China [2017YFC0211200, 2017YFC0211203]
  2. National Natural Science Foundation [51406140]
  3. National Engineering Laboratory for Mobile Source Emission Control Technology [NELMS2017A08]
  4. Natural Science Foundation of Hubei Province [2018CFB592]
  5. 111 Project [B17034]
  6. Innovative Research Team Development Program of Ministry of Education of China [IRT_17R83]

向作者/读者索取更多资源

The selective catalytic reduction (SCR) technology shall achieve a high NOx conversion efficiency but a limited reductant slip to satisfy the increasingly stringent Euro VI regulations. The physico-chemical model based non-dominated sorting genetic algorithm (NSGA-II) was applied here to gain the desired urea dosage feed ratio and achieve the optimal trade-off between NOx reduction and NH3 slip so that some benefits such as fuel and urea efficiency gains may be materialized; moreover, the dependence of the optimized solution on dynamic model was illustrated based on a sensitivity study and a reduced order one-state model was utilized to capture essential behaviors of the system under low computational burdens. Two different steady operating conditions were selected to validate optimal results from the model based NSGA-II method and conclude that they shall be in good agreement with acceptable errors. The optimization results were demonstrated by means of several typical cases where effects of the temperature and the space velocity on ammonia coverage ratio and NOx conversion efficiency were analyzed. In addition, the full load optimal maps for the engine were obtained based on our method to provide a reference or benchmark on the control system.

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