Study on Engine Characteristic Curves Drawing Method Based on BP Neural Network

Cui Xia Guo; Kang Liu; Wen Ling Xie; Shun Yong Zhou

doi:10.4028/www.scientific.net/AMR.591-593.593

Paper Titles

Delay-Dependent Robust Stability Analysis for Uncertain Nonlinear Systems
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An Approach to Determine Clamping Forces and Clamping Sequence of Thin-Walled Workpiece during Milling Process
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Application of Error Analysis Method in the Complex Vehicle Model
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Temperature Field Simulation of Ballscrew Whirlwind Milling
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Study on Engine Characteristic Curves Drawing Method Based on BP Neural Network
p.593

A New Method of Complex Logistics Planning Scheduling Based on Super Cubic Path Link Algorithm
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Study of the Transmission System of Spreading Powder Device of Direct Metal Sintering Rapid Prototyping Machine
p.602

Numerical Simulation and Studies of Temperature Rise within a High-Pressure Vessel during Refueling
p.606

Modeling and Simulation of the Hydraulic Height Adjustment System of Mobile Tail Based on AMESim
p.611

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Study on Engine Characteristic Curves Drawing Method Based on BP Neural Network

Abstract:

The BP neural network model based on PSO particle swarm optimization algorithm is analyzed in this paper. The engine speed and torque is the input of the network and the fuel consumption rate is output. Appling PSO algorithm to optimize BP neural network weights and threshold value, which makes the BP network having high precision nonlinear mapping relation, and then realize it by MATLAB software. Practice proves that the method is effective and it provides a new method of rendering engine characteristic curve fitting.