Simulation design of an Intelligent system for Automotive transmission Gearbox Based on FPGA

  • Azzad Bader SAEED
Keywords: Artificial intelligent system, Back-propagation neural network, FPGA, Levenberg-Marquardt training, Automotive transmission gearbox.


In this paper, an artificial  intelligent system has been designed, realized, and downloaded into  FPGA (Field Programmable Gate Array), which is used to control five speed ratio steps ( 1,2,3,4,5) of an electrically controlled type of  automotive transmission gearbox of a vehicle, the first speed ratio step (1) is characterized by the  highest torque, a lowest velocity, while, the  fifth step is characterized by the lowest torque, and highest velocity.

The Back-propagation neural network has been used as the intelligent system for the proposed system. The proposed neural network is composed from   eight neurons in the input layer, five neurons in the hidden layer, and five neurons in the output layer. For real downloading into the FPGA, Satlins and Satlin linear activation function has been used for the hidden and output layers respectively. The training function Trainlm ( Levenberg-Marqurdt training) has been used as a learning method for the proposed neural network, which it has a powerful algorithm.

 The proposed simulation system has been designed and downloaded into the FPGA using MATLAB and ISE Design Suit software packages.


Download data is not yet available.


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How to Cite
SAEED, A. B. (2018). Simulation design of an Intelligent system for Automotive transmission Gearbox Based on FPGA. EMITTER International Journal of Engineering Technology, 6(2), 395-411.