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Biodiesel Accommodations in Both Con...

Zhao, Junfeng.

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Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains./
作者:	Zhao, Junfeng.
面頁冊數:	206 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
Contained By:	Dissertation Abstracts International77-03B(E).
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3729476
ISBN:	9781339153322

Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains.
Zhao, Junfeng.

Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains. - 206 p.

Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.

Thesis (Ph.D.)--The Ohio State University, 2015.

This dissertation investigated biodiesel's accommodations in both conventional diesel engines and diesel-electric hybrid powertrains.

ISBN: 9781339153322Subjects--Topical Terms:

649730
Mechanical engineering.

Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains.
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100 1 $a Zhao, Junfeng. $3 3181535
245 1 0 $a Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains.
300 $a 206 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
500 $a Adviser: Junmin Wang.
502 $a Thesis (Ph.D.)--The Ohio State University, 2015.
520 $a This dissertation investigated biodiesel's accommodations in both conventional diesel engines and diesel-electric hybrid powertrains.
520 $a To facilitate the fuel property adaptive control, two types of onboard biodiesel blend-level estimation strategies were proposed. Firstly, a steady-state fuel property estimator was designed by utilizing the information of fuel-dependent, common-rail natural frequency, which can be extracted from the measurement of a common-rail pressure sensor. The differences of rail natural frequencies of diesel, biodiesel, gasoline, and ethanol were compared, and these differences are directly related to physical properties of the fuels. Secondly, in order to continuously monitor actual exhaust gas recirculation (EGR) levels while considering fuel property variation, a dynamic estimation strategy was proposed. An oxygen fraction dynamic model was developed for the engine with a dual-loop EGR system. Based on the model, an adaptive observer is designed for the joint estimations of air-path oxygen fractions and biodiesel blend level.
520 $a With the blend-level estimation, fuel adaptive control can be conducted to optimize the engine performance and emission level. A physics-based multi-phase combustion model was developed to predict ignition delay and CA50 for both diesel and biodiesel. And this model could be beneficial for fuel property adaptive feedback control. As quite a few fuel property adaptive control strategies in conventional powertrains have been proposed in literature, only a brief review was provided here. In this dissertation, the efforts were further extended to study biodiesel's influence on hybrid electric vehicle (HEV) powertrains coupled with diesel aftertreatment systems. A control-oriented model was developed by systematically incorporating HEV models and aftertreatment thermal dynamics models. The model was able to predict engine-out temperature and emissions, and to simulate the temperature dynamics in the aftertreatment systems. A novel aftertreatment system warm-up strategy featured by applying both early and late post injections was developed. Fuel properties' impacts on post injections were also studied through experimental results. A supervisory controller was designed to optimize the post injection ratio as well as the torque-split ratio of the HEV powertrain. With this approach, the warm-up time of aftertreatment systems can be significantly reduced and the selective catalytic reduction (SCR) system temperature can be kept within the desired range so that high emission reduction efficiency can be achieved. This method can also be compatible with biodiesel by updating the models according to the estimated blend-level information.
590 $a School code: 0168.
650 4 $a Mechanical engineering. $3 649730
650 4 $a Automotive engineering. $3 2181195
690 $a 0548
690 $a 0540
710 2 $a The Ohio State University. $b Mechanical Engineering. $3 1684523
773 0 $t Dissertation Abstracts International $g 77-03B(E).
790 $a 0168
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3729476