國立虎尾科技大學 |

Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles./
作者:	Zhang, Guoguang.
面頁冊數:	1 online resource (156 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
標題:	Mechanical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780355661675

Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles.
Zhang, Guoguang.

Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles. - 1 online resource (156 pages)

Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.

Thesis (Ph.D.)--The Ohio State University, 2017.

Includes bibliographical references

With the fast development of batteries, sensors, and electric motors in the past decade, the ground vehicles are being increasingly electrified. With more sensors and actuators being equipped, they may suffer from increased possibility of sensor and actuator faults. This dissertation therefore addresses the fault estimation for sensors and actuators as well as fault-tolerant control for one type of electrified ground vehicle, i.e., the in-wheel motor electric vehicle.

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

Mode of access: World Wide Web

ISBN: 9780355661675Subjects--Topical Terms:

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

554714
Electronic books.

Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles.
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245 1 0 $a Fault Estimation and Fault-tolerant Control for In-wheel Motor Electric Vehicles.
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500 $a Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
500 $a Adviser: Junmin Wang.
502 $a Thesis (Ph.D.)--The Ohio State University, 2017.
504 $a Includes bibliographical references
520 $a With the fast development of batteries, sensors, and electric motors in the past decade, the ground vehicles are being increasingly electrified. With more sensors and actuators being equipped, they may suffer from increased possibility of sensor and actuator faults. This dissertation therefore addresses the fault estimation for sensors and actuators as well as fault-tolerant control for one type of electrified ground vehicle, i.e., the in-wheel motor electric vehicle.
520 $a First, a prototype in-wheel motor electric vehicle is presented and the experimental platform is discussed. Then the problem of sensor fault estimation and reconstruction of contaminated signal is studied. Vehicle yaw rate signal is chosen as the contaminated signal and a robust gain-scheduling observer is proposed accordingly. Second, the steering motor fault estimation approach is developed because steering motor faults always impose a great threat to vehicle stability and safety. Furthermore, fault-type identification is also considered, which can provide detailed information of the type and magnitude of the actuator fault. Last, to deal with actuator fault and recover the faulty vehicle, an active fault-tolerant control system is proposed for in-wheel motor electric vehicles. It uses a baseline controller to accommodate actuator faults and stabilize the faulty vehicle when an actuator fault occurs. Actuator fault is detected and estimated by the fault detection and diagnosis mechanism. After that, a proper reconfigurable controller is switched on to recover the faulty vehicle. The proposed sensor and actuator fault estimation approaches and active fault-tolerant control system have been validated through simulations in CarSim® and/or vehicle experimental tests on an electric vehicle. At the end, future work and directions are given, which may further address the problems discussed in this dissertation.
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 Engineering. $3 561152
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0537
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The Ohio State University. $b Mechanical Engineering. $3 1148711
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10760338 $z click for full text (PQDT)