Abstract
With the coming of massive application on autonomous vehicles, the safeness has been one of the features with highest development priority, which are considered in the design of automotive control systems. The development of intelligent sensors is an effective way to achieve this goal. For spark-ignition engines, the regualation of air fuel ratio and the control of engine speed are the keys to obtain reliable engine performance. This paper proposes a neural network (NN) based soft sensor scheme for air/fuel ratio sensor and crankshaft speed sensor, which are two important measurements for the control in spark-ignition engines. The modeling results show that satisfactory modeling performance can be obtained with moderate computational load.
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Acknowledgements
This research was financially supported by the Centre for Smart Grid and Information Convergence (CeSGIC) at **an Jiaotong-Liverpool University. The authors would like to thank all the parties concerned.
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Zhai, Y., Man, K.L., Lee, S., Xue, F. (2018). A Neural Network Based Soft Sensors Scheme for Spark-Ignitions Engines. In: Ao, SI., Kim, H., Castillo, O., Chan, AS., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2017. Springer, Singapore. https://doi.org/10.1007/978-981-10-7488-2_15
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DOI: https://doi.org/10.1007/978-981-10-7488-2_15
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