Pub Date : 2018-12-01DOI: 10.1109/edpc.2018.8658262
{"title":"2018 8th International Electric Drives Production Conference (E|DPC)","authors":"","doi":"10.1109/edpc.2018.8658262","DOIUrl":"https://doi.org/10.1109/edpc.2018.8658262","url":null,"abstract":"","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124048723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658294
A. Mayr, M. Weigelt, Johannes von Lindenfels, J. Seefried, M. Ziegler, A. Mahr, N. Urban, A. Kühl, F. Hüttel, J. Franke
Industry 4.0 (I4.0) is accompanied by a variety of technologies which offer great potential for optimizing the manufacturing of electric motors. However, the application of I4.0 technologies in this sector has hardly been examined yet. For determining I4.0 potentials in the electric motor production, a structured approach is required since the variety of sub-processes and production technologies results in a vast number of possible combinations. Therefore, this paper first compares different generic approaches for identifying, selecting and implementing I4.0 use cases. Building on this, a methodical approach is derived in order to tap the numerous I4.0 potentials within the electric motor production. On the one hand, use cases can be derived from current technological opportunities resulting from application examples and best practices in research and industry. On the other hand, concrete problems in critical manufacturing processes can give rise to the application of novel I4.0 solutions. By presenting a comprehensive overview of promising application scenarios, this paper mainly facilitates the identification of I4.0 potentials in the electric motor production from an opportunity-driven perspective. In addition to approaches directly addressing the electric motor production, concepts can be derived from related processes in other application domains. Examples are provided by outlining a selection of the presumably most relevant use cases. The results indicate that especially data-driven approaches, i.e. data analytics and machine learning, offer great potential in electric motor production. As an outlook, I4.0 potentials can also be disclosed from a problem-pull perspective, supplementing the opportunity-push approach of this paper.
{"title":"Electric Motor Production 4.0 – Application Potentials of Industry 4.0 Technologies in the Manufacturing of Electric Motors","authors":"A. Mayr, M. Weigelt, Johannes von Lindenfels, J. Seefried, M. Ziegler, A. Mahr, N. Urban, A. Kühl, F. Hüttel, J. Franke","doi":"10.1109/EDPC.2018.8658294","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658294","url":null,"abstract":"Industry 4.0 (I4.0) is accompanied by a variety of technologies which offer great potential for optimizing the manufacturing of electric motors. However, the application of I4.0 technologies in this sector has hardly been examined yet. For determining I4.0 potentials in the electric motor production, a structured approach is required since the variety of sub-processes and production technologies results in a vast number of possible combinations. Therefore, this paper first compares different generic approaches for identifying, selecting and implementing I4.0 use cases. Building on this, a methodical approach is derived in order to tap the numerous I4.0 potentials within the electric motor production. On the one hand, use cases can be derived from current technological opportunities resulting from application examples and best practices in research and industry. On the other hand, concrete problems in critical manufacturing processes can give rise to the application of novel I4.0 solutions. By presenting a comprehensive overview of promising application scenarios, this paper mainly facilitates the identification of I4.0 potentials in the electric motor production from an opportunity-driven perspective. In addition to approaches directly addressing the electric motor production, concepts can be derived from related processes in other application domains. Examples are provided by outlining a selection of the presumably most relevant use cases. The results indicate that especially data-driven approaches, i.e. data analytics and machine learning, offer great potential in electric motor production. As an outlook, I4.0 potentials can also be disclosed from a problem-pull perspective, supplementing the opportunity-push approach of this paper.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129596786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658293
Dominik Kißkalt, A. Mayr, Johannes von Lindenfels, J. Franke
The market volume of electric drives for industrial applications and electric mobility is increasing steadily. Thus, efficient ways for monitoring and optimizing the production of electric drives are gaining importance. Besides winding, joining or impregnation processes, machining operations have a high share in the production chain. However, developing a process monitoring system for machining centers can be a cost-intense matter due to the need of addressing a manifold and dynamic error-space. Therefore, this paper examines potentials of cost-efficient data-driven approaches for process monitoring of machining operations on the example of electric drive production. In this context, a flexible approach for detecting current operational states by means of supervised machine learning is proposed. Since labor-intense modeling of process models based on a priori knowledge and first principles gets dispensable, the basis for self-adapting monitoring solutions is laid. Diverse process parameters such as structure-borne sound or cutting forces are suitable to train process and behavioral models. By realizing a system for operational state detection without necessary access to control-internal data, a cost-efficient process monitoring of the often heterogeneous machinery in electric drive production is enabled.
{"title":"Towards a Data-Driven Process Monitoring for Machining Operations Using the Example of Electric Drive Production","authors":"Dominik Kißkalt, A. Mayr, Johannes von Lindenfels, J. Franke","doi":"10.1109/EDPC.2018.8658293","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658293","url":null,"abstract":"The market volume of electric drives for industrial applications and electric mobility is increasing steadily. Thus, efficient ways for monitoring and optimizing the production of electric drives are gaining importance. Besides winding, joining or impregnation processes, machining operations have a high share in the production chain. However, developing a process monitoring system for machining centers can be a cost-intense matter due to the need of addressing a manifold and dynamic error-space. Therefore, this paper examines potentials of cost-efficient data-driven approaches for process monitoring of machining operations on the example of electric drive production. In this context, a flexible approach for detecting current operational states by means of supervised machine learning is proposed. Since labor-intense modeling of process models based on a priori knowledge and first principles gets dispensable, the basis for self-adapting monitoring solutions is laid. Diverse process parameters such as structure-borne sound or cutting forces are suitable to train process and behavioral models. By realizing a system for operational state detection without necessary access to control-internal data, a cost-efficient process monitoring of the often heterogeneous machinery in electric drive production is enabled.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123867076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658359
A. Kampker, K. Kreisköther, M. Büning, Tom Möller, Sven Windau
Within the context of Industry 4.0, data is being recorded and collected at an increasing rate in the production environment of electric drives. On the one hand, the data serves the producer as a backup against potential failure induced returns. On the other hand, some of the recorded data is used specifically for data analytics methods with the expectation to generate additional information and thus knowledge through intelligent data aggregation and processing. In the latter case, i.e. the use of data analytics methods, there are several possibilities to identify use cases and to implement them in a later step. Use cases can be discovered and identified on the basis of actual problems, so they can be considered as problem-driven. Problems and challenges in current electric drive production are taken here as a possible starting point for the identification of use cases. It is also conceivable that future problems can be anticipated by, for example, expert knowledge. Therefore, actual problems can be prevented prematurely with data analytics. A completely different approach is to analyze the currently available data bases and develop possible use cases based on the existing data. Currently, there is no systematical approach to cover the use case implementation for electric drives holistically. Therefore, in this paper, the possible fields of tension of the use case identification, evaluation and implementation will be presented. In the second step, based on the findings, a systematical approach to identify, evaluate and eventually implement use cases will be derived. The approach will then be applied to the generic production process chain of electric motors. Within the application of the approach, the whole drive production process chain was systematically analyzed. Out of the variety of process steps, a total of three use cases were selected due to the availability of data or due to identified process instabilities. For each of these three process steps, a use case was identified by conducting interviews with experts and the process-related operators. Out of the three developed use cases, one is being implemented, following the systematic approach presented within this paper
{"title":"Exhaustive Data- and Problem-Driven use Case Identification and Implementation for Electric Drive Production","authors":"A. Kampker, K. Kreisköther, M. Büning, Tom Möller, Sven Windau","doi":"10.1109/EDPC.2018.8658359","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658359","url":null,"abstract":"Within the context of Industry 4.0, data is being recorded and collected at an increasing rate in the production environment of electric drives. On the one hand, the data serves the producer as a backup against potential failure induced returns. On the other hand, some of the recorded data is used specifically for data analytics methods with the expectation to generate additional information and thus knowledge through intelligent data aggregation and processing. In the latter case, i.e. the use of data analytics methods, there are several possibilities to identify use cases and to implement them in a later step. Use cases can be discovered and identified on the basis of actual problems, so they can be considered as problem-driven. Problems and challenges in current electric drive production are taken here as a possible starting point for the identification of use cases. It is also conceivable that future problems can be anticipated by, for example, expert knowledge. Therefore, actual problems can be prevented prematurely with data analytics. A completely different approach is to analyze the currently available data bases and develop possible use cases based on the existing data. Currently, there is no systematical approach to cover the use case implementation for electric drives holistically. Therefore, in this paper, the possible fields of tension of the use case identification, evaluation and implementation will be presented. In the second step, based on the findings, a systematical approach to identify, evaluate and eventually implement use cases will be derived. The approach will then be applied to the generic production process chain of electric motors. Within the application of the approach, the whole drive production process chain was systematically analyzed. Out of the variety of process steps, a total of three use cases were selected due to the availability of data or due to identified process instabilities. For each of these three process steps, a use case was identified by conducting interviews with experts and the process-related operators. Out of the three developed use cases, one is being implemented, following the systematic approach presented within this paper","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658365
J. Niemann, Christoph Eckermann, A. Schlegel, T. Büttner, J. Stoldt, M. Putz
Electro mobility represents a key concept in response to current trends in the mobility sector. Yet, strong uncertainties regarding future demand of electric vehicles pose major challenges for capacity planning and procurement. Current forecasts predict a total market share of electric vehicles between 3 % and 24 % in 2025. This paper presents a study that aims to shed light on the challenges of capacity planning. We provide insights on the requirements of volume flexibility and changeability in the production and purchasing of electrified powertrains. The study relies on expert interviews in the field of production and procurement. We interviewed 13 managers from three leading, premium German carmakers. The interviews were conducted using a semi-structured guide that addresses six hypotheses concerning market development, long-term capacity planning, identification and definition of courses of action, interdependencies between the production and the supplier, specifics of the production system for electrified powertrains, and access to resources. The study's results show that demand volatility of electrified vehicles is expected to persist for the next 5 years. Consequently, existing demand uncertainties lead to a high number of different planning scenarios. This challenges capacity planners to provide enough capacity by relying on flexibility or changeability measures. Differences in supplier structures further require automotive OEM to change their mindset and to implement new processes. Despite those substantial changes, however, the task of purchasing remains vital to prevent quality losses or significant cost increases. Lastly, we show the importance of integrating supplier and purchasing department capacity planning process. Our main results indicate the need for developing a decision support system. It supports supply chain capacity planning of electric drive trains in order to enable fast and efficient reactions to volatile volumes.
{"title":"Requirements for Volume Flexibility and Changeability in the Production of Electrified Powertrains","authors":"J. Niemann, Christoph Eckermann, A. Schlegel, T. Büttner, J. Stoldt, M. Putz","doi":"10.1109/EDPC.2018.8658365","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658365","url":null,"abstract":"Electro mobility represents a key concept in response to current trends in the mobility sector. Yet, strong uncertainties regarding future demand of electric vehicles pose major challenges for capacity planning and procurement. Current forecasts predict a total market share of electric vehicles between 3 % and 24 % in 2025. This paper presents a study that aims to shed light on the challenges of capacity planning. We provide insights on the requirements of volume flexibility and changeability in the production and purchasing of electrified powertrains. The study relies on expert interviews in the field of production and procurement. We interviewed 13 managers from three leading, premium German carmakers. The interviews were conducted using a semi-structured guide that addresses six hypotheses concerning market development, long-term capacity planning, identification and definition of courses of action, interdependencies between the production and the supplier, specifics of the production system for electrified powertrains, and access to resources. The study's results show that demand volatility of electrified vehicles is expected to persist for the next 5 years. Consequently, existing demand uncertainties lead to a high number of different planning scenarios. This challenges capacity planners to provide enough capacity by relying on flexibility or changeability measures. Differences in supplier structures further require automotive OEM to change their mindset and to implement new processes. Despite those substantial changes, however, the task of purchasing remains vital to prevent quality losses or significant cost increases. Lastly, we show the importance of integrating supplier and purchasing department capacity planning process. Our main results indicate the need for developing a decision support system. It supports supply chain capacity planning of electric drive trains in order to enable fast and efficient reactions to volatile volumes.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133754660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658341
A. Kampker, Patrick Treichel, K. Kreisköther, R. Pandey, M. Büning, Till Backes
Axial flux permanent magnet (AFPM) motors, also known as disc type or pancake motors, offer many advantageous characteristics like high power density, compact design and diverse possibilities of motor design. Although distinctly better in few aspects compared to radial flux motors, there are definite reasons why axial flux motors have not been able to dominate the market, e.g, difficulties in part fabrication and motor assembly. In the wake of the development of new materials, it is possible to partly overcome these difficulties and simultaneously increase the power/torque density of the axial flux machine. This paper focuses on the identification of nonmagnetic components in an axial flux permanent magnet motor and the fabrication of these nonmagnetic parts using alternative materials and new fabrication technologies. For this purpose, the important motor parts like stator, rotor and housing are theoretically analyzed and the possibility of using nonmagnetic materials to manufacture them is verified. This will help in reducing the weight of the motor, offering enhancement of torque and power density. Less magnetic parts may also lead to better efficiency, as the losses due to induced currents are reduced.
{"title":"Alternative Fabrication Strategies for the Production of Axial Flux Permanent Magnet Synchronous Motors for Enhanced Performance Characteristics","authors":"A. Kampker, Patrick Treichel, K. Kreisköther, R. Pandey, M. Büning, Till Backes","doi":"10.1109/EDPC.2018.8658341","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658341","url":null,"abstract":"Axial flux permanent magnet (AFPM) motors, also known as disc type or pancake motors, offer many advantageous characteristics like high power density, compact design and diverse possibilities of motor design. Although distinctly better in few aspects compared to radial flux motors, there are definite reasons why axial flux motors have not been able to dominate the market, e.g, difficulties in part fabrication and motor assembly. In the wake of the development of new materials, it is possible to partly overcome these difficulties and simultaneously increase the power/torque density of the axial flux machine. This paper focuses on the identification of nonmagnetic components in an axial flux permanent magnet motor and the fabrication of these nonmagnetic parts using alternative materials and new fabrication technologies. For this purpose, the important motor parts like stator, rotor and housing are theoretically analyzed and the possibility of using nonmagnetic materials to manufacture them is verified. This will help in reducing the weight of the motor, offering enhancement of torque and power density. Less magnetic parts may also lead to better efficiency, as the losses due to induced currents are reduced.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114565120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658272
Simon Strohmeyr, W. Schinköthe, Simon Gadegast
Aiming at high forces at low space in linear direct drives, favorable heat transfer conditions and high copper filling factors of the coils are of central importance [1]. For this reasons coils are mainly made of round copper wire and subsequently casted with impregnating resins or epoxy resins to increase stability and thermal conductivity. However, there are alternatives such as coils with rectangular wire, casted coils [2] or PCB (printed circuit boards) coils [3]. Due to the geometric design of linear direct drives PCB coils can be an alternative [4]. In this paper a coil in printed circuit board design is presented. The development and the process, from the selection of suitable PCB designs to optimization, assembly and comparison with conventionally round wire coils, is described. A linear direct drive is designed to compare the force-displacement characteristics and the increase of the temperature in static operation of the two types of coils. Slightly lower temperature of the overall system at the same mechanical motor parameters can be achieved with the PCB coil.
{"title":"Design of Printed Circuit Board Coils for Precision Engineering Linear Direct Drives","authors":"Simon Strohmeyr, W. Schinköthe, Simon Gadegast","doi":"10.1109/EDPC.2018.8658272","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658272","url":null,"abstract":"Aiming at high forces at low space in linear direct drives, favorable heat transfer conditions and high copper filling factors of the coils are of central importance [1]. For this reasons coils are mainly made of round copper wire and subsequently casted with impregnating resins or epoxy resins to increase stability and thermal conductivity. However, there are alternatives such as coils with rectangular wire, casted coils [2] or PCB (printed circuit boards) coils [3]. Due to the geometric design of linear direct drives PCB coils can be an alternative [4]. In this paper a coil in printed circuit board design is presented. The development and the process, from the selection of suitable PCB designs to optimization, assembly and comparison with conventionally round wire coils, is described. A linear direct drive is designed to compare the force-displacement characteristics and the increase of the temperature in static operation of the two types of coils. Slightly lower temperature of the overall system at the same mechanical motor parameters can be achieved with the PCB coil.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122670234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658307
G. B. Mariani, N. Voyer
This paper investigates the simulation of a sensorless speed control method with estimates the position and the speed of a synchronous reluctance machine (SyncRM). Speed control implements Field Oriented Control (FOC)., fed with estimated speed and position. The method combines two different estimators. First., a Luenberger observer estimates the load torque of the machine from the mechanical model of the machine., knowing the value of the inertia coefficient and the dynamic friction coefficient. Then, a Kalman filter estimates the speed and the position of the machine., from differential state equations resulting from the analytical (electrical) model of the machine in the rotational reference frame, taking benefit of the estimated load torque. The robustness of the method was verified by Matlab/Simulink simulation for different speed and torque profiles., against parameter errors of the electrical (inductance and resistance) and mechanical (inertia and dynamic friction) models of a 5kW machine
{"title":"Robustness Evaluation of a Sensorless Control of Synchronous Reluctance Motor with a Kalman Filter & a Luenberger Observer","authors":"G. B. Mariani, N. Voyer","doi":"10.1109/EDPC.2018.8658307","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658307","url":null,"abstract":"This paper investigates the simulation of a sensorless speed control method with estimates the position and the speed of a synchronous reluctance machine (SyncRM). Speed control implements Field Oriented Control (FOC)., fed with estimated speed and position. The method combines two different estimators. First., a Luenberger observer estimates the load torque of the machine from the mechanical model of the machine., knowing the value of the inertia coefficient and the dynamic friction coefficient. Then, a Kalman filter estimates the speed and the position of the machine., from differential state equations resulting from the analytical (electrical) model of the machine in the rotational reference frame, taking benefit of the estimated load torque. The robustness of the method was verified by Matlab/Simulink simulation for different speed and torque profiles., against parameter errors of the electrical (inductance and resistance) and mechanical (inertia and dynamic friction) models of a 5kW machine","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128105012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658276
Maximilian Volkan Baloglu, K. Willner
The specific design of components like rotor and stator as sheet-layered lamination stacks results in a structural behavior that is heavily dependent on the sheet interactions on the microscale. Due to the manufacturing process, these thin laminations may be just stacked and held together e.g. by welding or clamps, such that frictional contact of rough surfaces between single sheets is taking place and significantly affects the overall deformation behavior. Here, the elastic anisotropic, more precisely transversely isotropic, material parameters describing these lamination stacks are identified with the help of the homogenization taking efficiently care of the microstructure. For this purpose, different constitutive contact laws in normal direction capturing the sheet interactions by a penalty formulation and their effect on the macroscopic quantities are presented to emphasize the importance of this model parameter. Furthermore, it is shown that the derived stress-strain relation is identical to results of a numerical homogenization, where a representative volume element is simulated by the Finite-Element method incorporating Zero-Thickness elements for the contact simulation. The numerical results are finally compared to experiments showing a good accordance.
{"title":"Influence of the Constitutive Contact Law on the Anisotropic Material Parameters of Sheet-Layered Lamination Stacks","authors":"Maximilian Volkan Baloglu, K. Willner","doi":"10.1109/EDPC.2018.8658276","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658276","url":null,"abstract":"The specific design of components like rotor and stator as sheet-layered lamination stacks results in a structural behavior that is heavily dependent on the sheet interactions on the microscale. Due to the manufacturing process, these thin laminations may be just stacked and held together e.g. by welding or clamps, such that frictional contact of rough surfaces between single sheets is taking place and significantly affects the overall deformation behavior. Here, the elastic anisotropic, more precisely transversely isotropic, material parameters describing these lamination stacks are identified with the help of the homogenization taking efficiently care of the microstructure. For this purpose, different constitutive contact laws in normal direction capturing the sheet interactions by a penalty formulation and their effect on the macroscopic quantities are presented to emphasize the importance of this model parameter. Furthermore, it is shown that the derived stress-strain relation is identical to results of a numerical homogenization, where a representative volume element is simulated by the Finite-Element method incorporating Zero-Thickness elements for the contact simulation. The numerical results are finally compared to experiments showing a good accordance.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126719861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/EDPC.2018.8658286
Jing Zhang, D. Spath, Ye He, A. Boronka
In the booming market of electrified mobility, product cost plays a crucial role for the competiveness of electric vehicles. Approximately 70% of the product costs are determined in the product development phase. Therefore, a cost evaluation of the product design in the development stage is necessary to check the achievement of cost target and if needed to modify the design as early as possible. To get a holistic view, not only the material cost, but also the manufacturing cost have to be taken into consideration. This work presents an approach to evaluate the cost of lamination stacks (stacking cost not included) used in electric traction motors of electric or hybrid vehicles. By following design of the lamination, the stamping process is modularized, which has an influence on the raw material utilization and manufacturing cost. Minimum cost of laminations can be achieved by increasing raw material utilization and decreasing manufacturing cost. The proposed model is developed for lamination cost estimation based on an optimum production decision, which is determined by selecting suitable stamping machine and proper mold design. The relationship between lamination design and the stamping process in terms of cost is illustrated under the condition of a fixed production volume. Finally, the influences of design changes on lamination costs are analyzed and the significance of this model is demonstrated.
{"title":"Cost-Efficient Selection of Stamping Machines for Lamination Production in the Electric Traction Motor Application","authors":"Jing Zhang, D. Spath, Ye He, A. Boronka","doi":"10.1109/EDPC.2018.8658286","DOIUrl":"https://doi.org/10.1109/EDPC.2018.8658286","url":null,"abstract":"In the booming market of electrified mobility, product cost plays a crucial role for the competiveness of electric vehicles. Approximately 70% of the product costs are determined in the product development phase. Therefore, a cost evaluation of the product design in the development stage is necessary to check the achievement of cost target and if needed to modify the design as early as possible. To get a holistic view, not only the material cost, but also the manufacturing cost have to be taken into consideration. This work presents an approach to evaluate the cost of lamination stacks (stacking cost not included) used in electric traction motors of electric or hybrid vehicles. By following design of the lamination, the stamping process is modularized, which has an influence on the raw material utilization and manufacturing cost. Minimum cost of laminations can be achieved by increasing raw material utilization and decreasing manufacturing cost. The proposed model is developed for lamination cost estimation based on an optimum production decision, which is determined by selecting suitable stamping machine and proper mold design. The relationship between lamination design and the stamping process in terms of cost is illustrated under the condition of a fixed production volume. Finally, the influences of design changes on lamination costs are analyzed and the significance of this model is demonstrated.","PeriodicalId":358881,"journal":{"name":"2018 8th International Electric Drives Production Conference (EDPC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126028528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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