Research on control strategy for Engine of Hybrid Tracked Bulldozer

Hong Wang; Qiang Song; Pu Zeng; Ping Zhao

doi:10.1109/ITEC-AP.2014.6940977

Research on control strategy for Engine of Hybrid Tracked Bulldozer

Hong Wang, Qiang Song^*, Pu Zeng, Ping Zhao

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In order to solve the problem in parameter optimization of control strategy for Engine of Hybrid Tracked Bulldozer, a new method is put forward based on a multidisciplinary design optimization. Based on the optimization design, the power train system model of the bulldozer for the Engine control strategy parameter optimization that took the minimum fuel consumption as objective function was established. The optimization took parameters of the engine control strategy as design variables and took the working area of the engine speed and power as the constraints. Then, the optimization problem is solved by means of adaptive genetic algorithm. Through optimization, the fuel consumption reduces 3.6% further more under a certain operating mode.

Original language	English
Title of host publication	IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479942398
DOIs	https://doi.org/10.1109/ITEC-AP.2014.6940977
Publication status	Published - 30 Oct 2014
Event	2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Beijing, China Duration: 31 Aug 2014 → 3 Sept 2014

Publication series

Name	IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings

Conference

Conference	2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014
Country/Territory	China
City	Beijing
Period	31/08/14 → 3/09/14

Keywords

Genetic Algorithm
Hybrid tracked bulldozer
engine control strategy
fuel economy
parameter optimization

Access to Document

10.1109/ITEC-AP.2014.6940977

Cite this

Wang, H., Song, Q., Zeng, P., & Zhao, P. (2014). Research on control strategy for Engine of Hybrid Tracked Bulldozer. In IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings Article 6940977 (IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITEC-AP.2014.6940977

Wang, Hong ; Song, Qiang ; Zeng, Pu et al. / Research on control strategy for Engine of Hybrid Tracked Bulldozer. IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. (IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings).

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abstract = "In order to solve the problem in parameter optimization of control strategy for Engine of Hybrid Tracked Bulldozer, a new method is put forward based on a multidisciplinary design optimization. Based on the optimization design, the power train system model of the bulldozer for the Engine control strategy parameter optimization that took the minimum fuel consumption as objective function was established. The optimization took parameters of the engine control strategy as design variables and took the working area of the engine speed and power as the constraints. Then, the optimization problem is solved by means of adaptive genetic algorithm. Through optimization, the fuel consumption reduces 3.6% further more under a certain operating mode.",

keywords = "Genetic Algorithm, Hybrid tracked bulldozer, engine control strategy, fuel economy, parameter optimization",

author = "Hong Wang and Qiang Song and Pu Zeng and Ping Zhao",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 ; Conference date: 31-08-2014 Through 03-09-2014",

year = "2014",

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doi = "10.1109/ITEC-AP.2014.6940977",

language = "English",

series = "IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings",

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Wang, H, Song, Q, Zeng, P & Zhao, P 2014, Research on control strategy for Engine of Hybrid Tracked Bulldozer. in IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings., 6940977, IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014, Beijing, China, 31/08/14. https://doi.org/10.1109/ITEC-AP.2014.6940977

Research on control strategy for Engine of Hybrid Tracked Bulldozer. / Wang, Hong; Song, Qiang; Zeng, Pu et al.
IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 6940977 (IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research on control strategy for Engine of Hybrid Tracked Bulldozer

AU - Wang, Hong

AU - Song, Qiang

AU - Zeng, Pu

AU - Zhao, Ping

PY - 2014/10/30

Y1 - 2014/10/30

N2 - In order to solve the problem in parameter optimization of control strategy for Engine of Hybrid Tracked Bulldozer, a new method is put forward based on a multidisciplinary design optimization. Based on the optimization design, the power train system model of the bulldozer for the Engine control strategy parameter optimization that took the minimum fuel consumption as objective function was established. The optimization took parameters of the engine control strategy as design variables and took the working area of the engine speed and power as the constraints. Then, the optimization problem is solved by means of adaptive genetic algorithm. Through optimization, the fuel consumption reduces 3.6% further more under a certain operating mode.

AB - In order to solve the problem in parameter optimization of control strategy for Engine of Hybrid Tracked Bulldozer, a new method is put forward based on a multidisciplinary design optimization. Based on the optimization design, the power train system model of the bulldozer for the Engine control strategy parameter optimization that took the minimum fuel consumption as objective function was established. The optimization took parameters of the engine control strategy as design variables and took the working area of the engine speed and power as the constraints. Then, the optimization problem is solved by means of adaptive genetic algorithm. Through optimization, the fuel consumption reduces 3.6% further more under a certain operating mode.

KW - Genetic Algorithm

KW - Hybrid tracked bulldozer

KW - engine control strategy

KW - fuel economy

KW - parameter optimization

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DO - 10.1109/ITEC-AP.2014.6940977

M3 - Conference contribution

AN - SCOPUS:84916212687

T3 - IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings

BT - IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014

Y2 - 31 August 2014 through 3 September 2014

ER -

Wang H, Song Q, Zeng P, Zhao P. Research on control strategy for Engine of Hybrid Tracked Bulldozer. In IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 6940977. (IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings). doi: 10.1109/ITEC-AP.2014.6940977

Research on control strategy for Engine of Hybrid Tracked Bulldozer

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