國立虎尾科技大學 |

Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern./
作者:	Qi, Wei.
面頁冊數:	1 online resource (173 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
Contained By:	Dissertation Abstracts International78-02B(E).
標題:	Mechanical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369019391

Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern.
Qi, Wei.

Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern. - 1 online resource (173 pages)

Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

The control strategy of a hybrid electric vehicle (HEV) has been an active research area in the past decades. The main goal of the optimal control strategy is to maximize the fuel economy and minimize exhaust emissions while also satisfying the expected vehicle performance. Dynamic programming (DP) is an algorithm capable of finding the global optimal solution of HEV operation. However, DP cannot be used as a real-time control approach as it requires pre-known driving information. The equivalent consumption minimization strategy (ECMS) is a real-time control approach, but it always results in local optima due to the non-convex cost function. In my research, a ECMS with DP combined model (ECMSwDP) was proposed, which was a compromise between optimality and real-time capability. In this approach, the optimal equivalent factor (lambda) for a real-time ECMS controller can be derived using ECMSwDP for a given driving condition. The optimal lambda obtained using ECMSwDP was further processed to derive the lambda map, which was a function of vehicle operation and driving information. Six lambda maps were generated corresponding to the developed representative driving patterns. At each distance segment of a drive cycle, the suitable lambda value is available from one of the six lambda maps based on the identified driving pattern and current vehicle operation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369019391Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern.
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245 1 0 $a Development of Real-time Optimal Control Strategy of Hybrid Transit Bus Based on Predicted Driving Pattern.
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300 $a 1 online resource (173 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
500 $a Adviser: Hailin Li.
502 $a Thesis (Ph.D.) $c West Virginia University $d 2016.
504 $a Includes bibliographical references
520 $a The control strategy of a hybrid electric vehicle (HEV) has been an active research area in the past decades. The main goal of the optimal control strategy is to maximize the fuel economy and minimize exhaust emissions while also satisfying the expected vehicle performance. Dynamic programming (DP) is an algorithm capable of finding the global optimal solution of HEV operation. However, DP cannot be used as a real-time control approach as it requires pre-known driving information. The equivalent consumption minimization strategy (ECMS) is a real-time control approach, but it always results in local optima due to the non-convex cost function. In my research, a ECMS with DP combined model (ECMSwDP) was proposed, which was a compromise between optimality and real-time capability. In this approach, the optimal equivalent factor (lambda) for a real-time ECMS controller can be derived using ECMSwDP for a given driving condition. The optimal lambda obtained using ECMSwDP was further processed to derive the lambda map, which was a function of vehicle operation and driving information. Six lambda maps were generated corresponding to the developed representative driving patterns. At each distance segment of a drive cycle, the suitable lambda value is available from one of the six lambda maps based on the identified driving pattern and current vehicle operation.
520 $a An adaptive ECMS (A-ECMS) model with a driving pattern identification model is developed to achieve the real-time optimal control for a HEV. A-ECMS was capable of controlling the ratio of power provided by the ICE and battery of a hybrid vehicle by selecting the lambda based on the identified lambda map. The effect on fuel consumption of the control strategies developed using the rule-based controller, ECMSwDP, A-ECMS, and DP was simulated using the parallel hybrid bus model developed in this research. The control strategies developed using A-ECMS are able to significantly improve the fuel economy while maintaining the battery charge sustainability. The corrected fuel economy observed with A-ECMS with a penalty function and the average lambda of RDPs was 5.55%, 13.67%, and 19.19% gap to that observed with DP when operated over the Beijing cycle, WVU-CSI cycle, and the actual transit bus route, respectively. The corrected fuel economy observed with A-ECMS with lambda maps of the RDPs was 4.83%, 10.61%, and 14.33% gap to that observed with DP when operated on the Beijing cycle, WVU-CSI cycle, and actual transit bus route, respectively. The simulation results demonstrated that the proposed A-ECMS approaches have the capability to achieve real time suboptimal control of a HEV while maintaining the charge sustainability of the battery.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Automotive engineering. $3 1104081
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
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690 $a 0540
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710 2 $a West Virginia University. $b Mechanical Engineering. $3 1180236
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