項目詳細信息 Detalhes de Projeto

項目詳細信息
Detalhes de Projeto
檔案編號
No. de
Arquivo
申請實體
Entidade Requerente
項目負責人
Responsáve
l de Projeto
項目名稱
Designação de Projeto
019/2007/A
澳門大學
王百鍵
基於數據及指定值對汽車動力性能
建模及優化
The automotive engine dynamic performance usually refers to engine torque response
and engine time-dependent performance which are significantly affected by the setup of
control parameters in the electronic control unit (ECU). The performance model of a
modern automotive engine is a complex multi-variable function, so it is very difficult to
be found. Moreover, the performance model is also engine dependent. Current practice of
ECU tune-up relies on the experience of the automotive engineer. The ECU tune-up is
usually done by trial-and-error method. Obviously the current practice costs a large
amount of time and money. The problem can be solved by developing a mathematical
engine model and computer optimizer for engine setup optimization. This report presents
項目摘要
an investigation on a novel least-squares support vector machines (LS-SVM) plus data
Sumário de preprocessing techniques, such as committee machines, nonlinear regression and kernel
Projeto
principal components analysis, for modeling of engine dynamic performance under
numerical and nominal data. Direct search techniques, such as Genetic algorithm (GA)
and Particle Swarm Optimization, are then applied to the engine models built in order to
automatically determine the optimal ECU setup subject to user-specific constraints. All of
the above techniques mentioned are emerging artificial intelligence techniques. As the
topic of engine dynamic performance tune-up is very wide, this project only studied the
problems of engine torque & power performance and idle-speed performance under
different operating
&
environmental conditions
and user-defined
constraints.
Experimental results show that the LS-SVM, data preprocessing and optimization
techniques can successfully produce optimal automotive engine performance.
結果類型
Tipo de
Resultado
主要完成者
結果名稱
結果說明
Designação de Resultado Agente Principal Explicação de Resultado
結果被引
用或收
錄情況
Situação de
Citação ou
Inclusão de
Resultado
Referred
international
journal paper
Automotive Engine Idle
Speed Control
Optimization Using
Least Squares Support
Vector Machine and
Genetic Algorithm
P.K. Wong,
L.M. Tam,
K. Li,
H.C. Wong
International Journal of
Intelligent Computing and
Cybernetics, Vol.1, No. 4,
pp. 598-616, 2008
Referred
international
journal paper
Data Preprocessing and
Modelling of
Electronically-Controlle
d Automotive Engine
Power Performance
using Kernel Principal
Components Analysis
and Least-Square
Support Vector
Machines
Engine Idle-speed
System Modelling and
Control Optimization
Using Artificial
Intelligence
Pak Kin Wong,
Chi Man Vong,
Lap Mou Tam,
Ke Li
International Journal of
Vehicle Systems
Modelling and Testing,
Vol.3, No.4, pp.312-330,
2008.
P.K. Wong,
L.M. Tam,
K. Li,
C.M. Vong
Referred
international
journal paper
Case-based Adaptation
for Automotive Engine
Electronic Control Unit
Calibration
Chi man Vong,
Pak kin Wong
Proceedings of the
Institution of Mechanical
Engineers, Part D, Journal
of Automobile
Engineering, Vol. 224,
No.1, pp.55-72, 2010.
Expert Systems with
Applications, Vol. 37,
Issue 4, pp.3184-3194,
2010.
Referred
international
journal paper
Compensation Map
Calibration of Engine
Management Systems
using Bio-inspired
Computing
Pak Kin Wong,
C.M. Vong
Regional
conference
paper
Prediction of Car Engine
Brake Specific Fuel
Consumption Using
Support Vector
Machines
Engine Idle Speed
System Calibration and
Optimization Using
Least Squares Support
Vector Machine and
Genetic Algorithm
Wong Pak-kin
Referred
international
journal paper
International
conference
paper
International
conference
paper
International
conference
paper
International
conference
paper
Li Ke,
Wong Pak-kin,
Tam, Lap-mou,
H. C. Wong
A Study on Online
LS-SVM for Modeling
of
Electronically-controlled
Automotive Engine
Performance
Incremental Modelling
of Automotive Engine
Performance using
LS-SVM
Chi-man VONG,
Pak-kin WONG,
Ke LI,
Rui ZHANG
Modelling and
Prediction of
Spark-ignition Engine
Power Performance
using Incremental Least
Squares Support Vector
Machines
P. K. WONG,
Chi-man Vong,
H. C. WONG
Ke Li
C.M. Vong,
P.K. Wong,
R. Zhang
Journal of Algorithms in
Cognition, Informatics
and Logic, Special Issue
on Bio-inspired
Computing: Theory and
Applications, 2009.
China, Written-paper, 14th
China Symposium on
Information Theory, Dec.
2007.
Germany, Oral and poster
presentation, International
Federation of Automotive
Engineering Societies
(FISITA) 32nd World
Automotive Congress,
Sept. 2008.
Japan, Oral presentation,
9th International
Symposium on Advanced
Vehicle Control, 6-9 Oct.,
2008.
China, Oral presentation,
2009 IEEE International
Conference on
Information and
Automation, China,
22-25th June 2009.
Hong Kong-Macau, Oral
presentation, 2nd
International Symposium
on Computational
Mechanics and 12th
International Conference on
Enhancement and
Promotion of
Computational Methods in
Engineering and Science,
30th Nov.-3rd Dec., 2009.
人才培養
數目
博士或以上
Doutor ou mais
碩士
Mestrado
學士或以下
Licenciado ou menos
1
2
3
Número de
Formação de
Pessoais
研究結果
Resultado
de Estudo
樣品
Amostra
成品
Obra Concluída
產品
Produto
-
-
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*註︰
*Obs.:
(1) 由於申報獎勵、發表著作和申請專利需時，此項目可能還有一些成果未被列出，科學技術
發展基金將在收到新的成果資料後，進行更新。
(1)
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