Research on the Parameter Calibration of the Internal-Combustion Engine Work Process Simulation Model

Abstract:

The computer simulation technology of the work process of internal-combustion engine is the important measure to study the internal-combustion engine, but generally, because of the uncertainty of input parameters, the precision of the simulation model of the engine work process, which largely limits the application of the simulation model, so the parameters of the simulation model needs to be calibrated. Taking the work process of the certain one type turbocharging diesel engine as the example, and combining the genetic algorithm with the ant colony algorithm, the parameter combination which can satisfy the requirements of precision, is selected in this article to effectively reduce the simulation experiment times of parameter calibration, and realize the automatic calibration of the simulation model parameters. By comparing and analyzing the practical result of the experiment and the result of the simulation computation, the effectiveness of the algorithm has been validated in the article.

• Periodical: Advanced Materials Research (Volumes 308-310)
• Pages: 953-961
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.308-310.953
• Online since: August 2011
• Authors: Qing Yin Niu, Chao Fan, Xian Chen Wang, Yi Wu Zhao, Yu Cai Dong
• Keywords: Optimization Algorithm, Parameter Calibration, Work Process of Internal-Combustion Engine

References

[1] Ding J L, Chen Z Q, Yuan Z Z. On the combination of genetic algorithm and ant algorithm. Journal of Computer Research and Development. No. 40(9). P.1351-1356. (2003).

[2] Duan, Haibin. Principle and Application of Ant Colony Algorithm. Beijing: Science Press. P. 176-178. (2005).In Chinese.

[3] Huang, Shaorong. Genetic Algorithm and Applications. Computer Engineering Application Technology. No. 34. P.1874-1876. (2008). In Chinese.

[4] Marco Dorigo, L M Gambardella & Luca Maria. Ant colonies for the traveling salesman problem. Biosystems. No. 43(2). P.73-81. (1997).

DOI: 10.1016/s0303-2647(97)01708-5

[5] Wang, Xiancheng & Zhang, Gengyun et al. Car Internal-Combustion Engine Theory. Beijing: Weapon Industry Press. April of 2006. (2006). In Chinese.

[6] Xing, Wenxun & Xie, Jinxing. Modern Optimization Computation Method. Beijing: Tsinghua University Press. Aug of 2006. (1999). In Chinese.

[7] Xiong, Zhihui. Hardware/ Software Partitioning Based on Dynamic Combination of Genetic Algorithm and Ant Algorithm. Journal of Software. No. 16(4). P.505-506. (2005). In Chinese.

DOI: 10.1360/jos160503

[8] Yang, Li. Study on the Modeling and Simulation of the 6S60MC Marine Diesel Engine Work Process. Dalian: Master's Thesis of Dalian Maritime University. (2006). In Chinese.

[9] Yun, Qingyuan. Genetic Algorithm and Genetic Rules. Beijing: Metallurgical Industry Press. (1997). In Chinese.

[10] Zou, Zhenyu. Study on the Micro Simulation and Parameter Calibration of the Traffic System. Hangzhou: Master's Thesis of Zhejiang University. Aug of 2006. (2006). In Chinese.