Analysis on BMWS Automatic Transmission Problems

Article Preview

Abstract:

The article analyses the principles AT work, and a detailed analysis of BMW's automatic transmission failures, and maintenance process. Maintenance of other automatic transmission provides a certain degree of significance. It is made up of components such as pump, turbine and stator, which directly enter the engine power and torque, while a clutch role.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

186-189

Citation:

Online since:

June 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Xu qingwen, BMW 530 automatic transmission failures[J].www.atauto.com.cn.2011.02

Google Scholar

[2] CH EN Ran, CHEN Pei-fu, SUN Dong-ye, H U Feng-bin. Fuzzy Immune PID Controller in Sh ift of Dual C lutch T ransm ission Veh icle[J]. Contro lEng ineering of Ch ina.2011.11(06):764-769

Google Scholar

[3] S.E. Fahlman, C. Lebiere, The cascade-correlation learning architecture[M].Advances in Neural Information Processing systems, San Mateo, CA: Morgan Kaufmann, 1990(2):524–532.

Google Scholar

[4] L. Prechelt, Investigation of the CasCor family of learning algorithms[J].Neural Networks, 1997(10):885–896.

DOI: 10.1016/s0893-6080(96)00115-3

Google Scholar

[5] S. Sjogaard, Generalization in cascade-correlation networks [J].Proc. IEEE Signal Processing Workshop, 1992:59–68.

DOI: 10.1109/nnsp.1992.253707

Google Scholar

[6] Li Zhiguo (2009) Research on Chinese Word Segmentation and Text Classification in Distributed Text Knowledge Management, Chongqing University, Chongqing

Google Scholar

[7] Deerwester S, Dumais S T, Furnas G W, et al (1990) Indexing by latent semantic analysis, Journal of the American Society for Information Science, 41: 391-407

DOI: 10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9

Google Scholar

[8] Hofmann T (1999) Probabilistic latent semantic indexing, Proceedings of the 22nd International Conference on Research and Development in Information Retrieval, Berkeley

DOI: 10.1145/312624.312649

Google Scholar