{"created":"2023-06-19T11:42:51.359193+00:00","id":12160,"links":{},"metadata":{"_buckets":{"deposit":"0a1dd705-3cfc-4823-be95-28940ef3c736"},"_deposit":{"created_by":15,"id":"12160","owners":[15],"pid":{"revision_id":0,"type":"depid","value":"12160"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:00012160","sets":["366:640:641:924"]},"author_link":["39824","39822"],"item_7_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2017-09","bibliographicIssueDateType":"Issued"}}]},"item_7_contributor_61":{"attribute_name":"修士論文指導教員","attribute_value_mlt":[{"contributorNames":[{"contributorName":"石田, 宗秋","lang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"39824","nameIdentifierScheme":"WEKO"}]}]},"item_7_description_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_7_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"1.1 Background of the research  1.1.1 Brief classification of motor[1][2][3][4]  Motor is a kind of electrical machine which converts electrical energy into mechanical one. With recent development and improvement, the structure of motor is usually made up of rotor part and stator part. By classification of driving strategy. There are two kinds of motor, DC motor and AC motor. (1). DC motor: The driving current of DC motor is directcurrent. The motor has a commutator. It causes sparks when DC motor runs with large current. To avoid this problem, brushless DC motor[1] has been invented. But both of them(DC motor and brushless DC motor) require a complicated DC power supply system, which causes power losses when electricity power is alternated. (2). AC motor: The driving signal of AC motor is sinusoidal current. This kind of motor usually has three-phase currents. Each phase current is apart from each other by 120 degrees in space. In AC motors, there are two popular ones, induction motor and synchronous motor. In induction motor, rotor speed lags behind stator speed. This is named slip, and slip is the reason why induction motor cannot achieve high efficiency. Synchronous can be divided by rotor structure as wound rotor synchronous motor and PMSM(permanent magnet synchronous motor). The paper targets PMSM as the controlled plant. The structure of PMSM is introduced in detail within Chapter 2. The mentioned motor classification is shown in Fig.1.1 1.1.2 PMSM speed control strategy PMSM speed control system is complicated. Compared with brush DC motor speed control system, it is more difficult for PMSM to achieve high accuracy, stability and fast response. Nowadays, researchers and engineers are focusing on improving these characteristics for PMSM speed control system. There are mainly three achievements.There are mainly three achievements. There are mainly three achievements.There are mainly three achievements. (1). VVVF (Variable voltage frequency) Control[5] VVVF control strategy is an early speed control method for AC motors, including PMSM.It was firstly proposed to achieve AC motor speed control because it is a constant when supply voltage divided by motor frequency, if the flux is not altered. (2). DTC(Direct Torque Control)[6] DTC control strategy is a loop control method for AC motors. It was first proposed by Dr. Depenbrock in 1985. This kind of control strategy get electrical driving torque by calculating stator flux. (3). FOC (Field Oriented Control) [7][8] FOC control strategy was proposed by Siemens engineer in 1970s. From that time, vector control for AC motor has been applied into motor speed control field. With Park and Clerk transformation, this control strategy has been greatly imporved. In this paper, this control strategy has been applied. And will be introduced in Chapter 2. 1.1.3 PMSM position sensorless speed control strategy Position sensorless speed control strategy for PMSM reduces the whole system cost and makes the system be possible to work in high dust environment. There are a lot of methods to achieve sensorless control.The methods are classified according to the motor speed. (1). High-speed position sensorless method [9][10][11] High-speed position sensorless control method usually uses voltage and current which contain Back-EMF signals to estimate the position and speed information. By these estimationmations, position sensorless control is achieved in high-speed region. (2). Low-speed position sensorless method [12][13] Low-speed position sensorless control method usually injects small amplitude high frequency signal in d-axis. If the motor has salient pole, a large induced voltage happens. With this saliency of PMSM,it can achieve low-speed position sensorless control.  1.2 Aims of the study This study aims at IPMSM position sensorless control in low speed range with EKF(Extended Kalman Filter) As our former method cannot achieve low-speed range position sensorless control. EKF can solve the problem above to some extend. To achieve better system characteristics,a d-axis current random signal injection method with EKF is proposed, which makes EKF be able to achieve better IPMSM position sensorless control in low speed -range. 1.3 Comparison with former study The former method is EEMF Observer. This method can achieve IPMSM position sensorless control above 300rpm. 300rpm is defined as the boundary between high and low-speed region. By using d-axis current random signal injection method with EKF, IPMSM can achieve low-speed range position sensorless control.The lowest controlled speed is 0 rpm. To improve robustness to load torque, noise balanced matrix Q of EKF is compensated. 1.4 Composition of the paper　This paper is made up of the following 7 parts.  Chapter 1 is the abstract. It includes background and aims of the study and comparison with former one. Chapter 2 introduces about basic characteristics of PMSM, which includes PMSM construction, mathematics dynamics and FOC strategy. Chapter 3 discusses about EEMF Observer for PMSM position sensorless control, which is the former study method. After analyzing, the weakness of EEMF Observer is pointed out. Chapter 4 introduces EKF(Extended Kalman Filter) for IPMSM. Addtionally, d-axis current random signal injection method with EKF will be discussed in this part. Chapter 5 shows simulation results to prove the aims of this study. Chapter 6 is the conclusions according to the discussion and simulation results. Then,the future plan is given.","subitem_description_type":"Abstract"}]},"item_7_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"三重大学大学院 工学研究科 博士前期課程 電気電子工学専攻 電気システム工学講座","subitem_description_type":"Other"},{"subitem_description":"82p","subitem_description_type":"Other"}]},"item_7_publisher_30":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"三重大学"}]},"item_7_text_31":{"attribute_name":"出版者（ヨミ）","attribute_value_mlt":[{"subitem_text_value":"ミエダイガク"}]},"item_7_text_65":{"attribute_name":"資源タイプ（三重大）","attribute_value_mlt":[{"subitem_text_value":"Master's Thesis / 修士論文"}]},"item_7_version_type_15":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"WANG, YANKAI","creatorNameLang":"en"},{"creatorName":"オウ, ゲンカイ","creatorNameLang":"ja"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-10-18"}],"displaytype":"detail","filename":"2017ME001.pdf","filesize":[{"value":"2.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"2017ME001","url":"https://mie-u.repo.nii.ac.jp/record/12160/files/2017ME001.pdf"},"version_id":"9878f562-23f4-4999-a375-f4db3e4eea88"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"Research on PMSM Position Sensorless Control with EKF (Extended Kalman Filter)","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Research on PMSM Position Sensorless Control with EKF (Extended Kalman Filter)","subitem_title_language":"en"}]},"item_type_id":"7","owner":"15","path":["924"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-10-18"},"publish_date":"2018-10-18","publish_status":"0","recid":"12160","relation_version_is_last":true,"title":["Research on PMSM Position Sensorless Control with EKF (Extended Kalman Filter)"],"weko_creator_id":"15","weko_shared_id":-1},"updated":"2023-11-30T04:31:05.044689+00:00"}