{"title":"Finite Element Simulation-Based Design Optimization of Permanent Magnet Motors considering Drive Cycle","authors":"K. Kant, J. Kirtley, L. V. Iyer, Gerd Schlager","doi":"10.4271/14-10-02-0012","DOIUrl":"https://doi.org/10.4271/14-10-02-0012","url":null,"abstract":"","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78898664","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}
Chen Duan, Zhongyang Zhao, Caisheng Wang, Jianfei Chen, Matt Liao
{"title":"An Electric Vehicle Onboard Microgrid with Solar Panel for Battery Module Balancing and Vehicle-to-Grid Applications","authors":"Chen Duan, Zhongyang Zhao, Caisheng Wang, Jianfei Chen, Matt Liao","doi":"10.4271/14-10-02-0011","DOIUrl":"https://doi.org/10.4271/14-10-02-0011","url":null,"abstract":"","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"47 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89041161","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}
{"title":"Current-Sensing Techniques for Revenue Metering and for Detecting Direct Current Injection from Electric Vehicles: A Review","authors":"O. Mironenko, W. Kempton, F. Kiamilev","doi":"10.4271/14-10-02-0010","DOIUrl":"https://doi.org/10.4271/14-10-02-0010","url":null,"abstract":"","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"36 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82174209","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}
Liu Fang, Liu Xinyi, Su Weixing, Chen Hanning, He Maowei, Li Xiaodan
To realize a fast and high-precision online state-of-health (SOH) estimation of lithium-ion (Li-Ion) battery, this article proposes a novel SOH estimation method. This method consists of a new SOH model and parameters identification method based on an improved genetic algorithm (Improved-GA). The new SOH model combines the equivalent circuit model (ECM) and the data-driven model. The advantages lie in keeping the physical meaning of the ECM while improving its dynamic characteristics and accuracy. The improved-GA can effectively avoid falling into a local optimal problem and improve the convergence speed and search accuracy. So the advantages of the SOH estimation method proposed in this article are that it only relies on battery management systems (BMS) monitoring data and removes many assumptions in some other traditional ECM-based SOH estimation methods, so it is closer to the actual needs for electric vehicle (EV). By comparing with the traditional ECM-based SOH estimation method, the algorithm proposed in this article has higher accuracy, fewer identification parameters, and lower computational complexity.
{"title":"State-of-Health Online Estimation for Li-Ion Battery","authors":"Liu Fang, Liu Xinyi, Su Weixing, Chen Hanning, He Maowei, Li Xiaodan","doi":"10.4271/14-09-02-0012","DOIUrl":"https://doi.org/10.4271/14-09-02-0012","url":null,"abstract":"To realize a fast and high-precision online state-of-health (SOH) estimation of lithium-ion (Li-Ion) battery, this article proposes a novel SOH estimation method. This method consists of a new SOH model and parameters identification method based on an improved genetic algorithm (Improved-GA). The new SOH model combines the equivalent circuit model (ECM) and the data-driven model. The advantages lie in keeping the physical meaning of the ECM while improving its dynamic characteristics and accuracy. The improved-GA can effectively avoid falling into a local optimal problem and improve the convergence speed and search accuracy. So the advantages of the SOH estimation method proposed in this article are that it only relies on battery management systems (BMS) monitoring data and removes many assumptions in some other traditional ECM-based SOH estimation methods, so it is closer to the actual needs for electric vehicle (EV). By comparing with the traditional ECM-based SOH estimation method, the algorithm proposed in this article has higher accuracy, fewer identification parameters, and lower computational complexity.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"8 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82394085","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}
The variability of fuel economy (FE) is of significant importance as that of average FE to realize FE benefits of hybrid electric vehicles (HEVs) consistently by all users in the real world. Over the years, majority of the research has been focused on improving average FE overlooking the variability. Although in recent years few studies have been focused on the reduction of FE variability, no study has been concentrated to understand why certain design has lower FE variability as that of others. This article provides a detailed analysis to decipher the reasons for the FE variability in the real world. This study considered the optimum designs based on two established design optimization methodologies considering Toyota Prius non-plug-in hybrid as a base vehicle. This study analyses the impacts of the parameters of driving patterns and the operation of powertrains on FE variability. The study explains that comparatively bigger internal combustion engine (ICE) in combination with the optimum sizes of generator motor and battery could lead to lower FE variability in the real world due to lesser time of operation of ICE to charge the battery.
{"title":"Understanding Real-World Variability of Hybrid Electric Vehicle Fuel Economy","authors":"Hillol K. Roy, A. McGordon, P. Jennings","doi":"10.4271/14-09-02-0011","DOIUrl":"https://doi.org/10.4271/14-09-02-0011","url":null,"abstract":"The variability of fuel economy (FE) is of significant importance as that of average FE to realize FE benefits of hybrid electric vehicles (HEVs) consistently by all users in the real world. Over the years, majority of the research has been focused on improving average FE overlooking the variability. Although in recent years few studies have been focused on the reduction of FE variability, no study has been concentrated to understand why certain design has lower FE variability as that of others. This article provides a detailed analysis to decipher the reasons for the FE variability in the real world. This study considered the optimum designs based on two established design optimization methodologies considering Toyota Prius non-plug-in hybrid as a base vehicle. This study analyses the impacts of the parameters of driving patterns and the operation of powertrains on FE variability. The study explains that comparatively bigger internal combustion engine (ICE) in combination with the optimum sizes of generator motor and battery could lead to lower FE variability in the real world due to lesser time of operation of ICE to charge the battery.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"41 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75293231","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}
The equivalent consumption minimization strategy (ECMS) is a promising energy management approach to low-fuel economy with the outstanding features of high efficiency. In this article, an optimal ECMS by Improved Genetic Algorithm (IGA) is proposed. To this end, we improved the genetic algorithm (GA) from the coding method, initialization mode, and cross and mutation process. And based on the comprehensive energy consumption and Pontryagin’s minimum principle, the equivalent factor was derived. The IGA was used to optimize the equivalent factor. To evaluate the performance of the proposed energy management strategy (EMS), the average efficiency of the engine and the motor was analyzed in an urban area, high-speed area, and the whole area. The comprehensive fuel consumption was used as the energy consumption index, and the battery capacity loss under the transient conditions was amplified to 10 years as the evaluation battery life index. The simulation results show that under the New European Driving Cycle (NEDC), the proposed strategy improves the fuel economy and battery life index by 14.64% and 36.76%, respectively, compared with the rule-based EMS.
{"title":"Optimal Equivalent Consumption Minimization Strategy for Plug-In Hybrid Electric Vehicle with Improved Genetic Algorithm","authors":"Changyin Wei, Yong Chen, Xiuxiu Sun, Yue Zhang","doi":"10.4271/14-09-02-0009","DOIUrl":"https://doi.org/10.4271/14-09-02-0009","url":null,"abstract":"The equivalent consumption minimization strategy (ECMS) is a promising energy management approach to low-fuel economy with the outstanding features of high efficiency. In this article, an optimal ECMS by Improved Genetic Algorithm (IGA) is proposed. To this end, we improved the genetic algorithm (GA) from the coding method, initialization mode, and cross and mutation process. And based on the comprehensive energy consumption and Pontryagin’s minimum principle, the equivalent factor was derived. The IGA was used to optimize the equivalent factor. To evaluate the performance of the proposed energy management strategy (EMS), the average efficiency of the engine and the motor was analyzed in an urban area, high-speed area, and the whole area. The comprehensive fuel consumption was used as the energy consumption index, and the battery capacity loss under the transient conditions was amplified to 10 years as the evaluation battery life index. The simulation results show that under the New European Driving Cycle (NEDC), the proposed strategy improves the fuel economy and battery life index by 14.64% and 36.76%, respectively, compared with the rule-based EMS.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"20 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79434191","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}
Torque interruption and shift jerk are the two main issues that occur during the gear-shifting process of electric-driven mechanical transmission. Herein, a time-optimal coordination control strategy between the the drive motor and the shift motor is proposed to eliminate the impacts between the sleeve and the gear ring. To determine the optimal control law, first, a gear-shifting dynamic model is constructed to capture the drive motor and shift motor dynamics. Next, the time-optimal dual synchronization control for the drive motor and the time-optimal position control for the shift motor are designed. Moreover, a switched control for the shift motor between a bang-off-bang control and a receding horizon control (RHC) law is derived to match the time-optimal dual synchronization control strategy of the drive motor. Finally, two case studies are conducted to validate the bang-off-bang control and RHC. In addition, the method to obtain the appropriate parameters of the drive motor and shift motor is analyzed according to the coordination control method.
{"title":"Time-Optimal Coordination Control for the Gear-Shifting Process in Electric-Driven Mechanical Transmission (Dog Clutch) without Impacts","authors":"Ziwang Lu, Guangyu Tian, S. Onori","doi":"10.4271/14-09-02-0010","DOIUrl":"https://doi.org/10.4271/14-09-02-0010","url":null,"abstract":"Torque interruption and shift jerk are the two main issues that occur during the gear-shifting process of electric-driven mechanical transmission. Herein, a time-optimal coordination control strategy between the the drive motor and the shift motor is proposed to eliminate the impacts between the sleeve and the gear ring. To determine the optimal control law, first, a gear-shifting dynamic model is constructed to capture the drive motor and shift motor dynamics. Next, the time-optimal dual synchronization control for the drive motor and the time-optimal position control for the shift motor are designed. Moreover, a switched control for the shift motor between a bang-off-bang control and a receding horizon control (RHC) law is derived to match the time-optimal dual synchronization control strategy of the drive motor. Finally, two case studies are conducted to validate the bang-off-bang control and RHC. In addition, the method to obtain the appropriate parameters of the drive motor and shift motor is analyzed according to the coordination control method.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"18 4 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85193387","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}
Electric vehicles equipped with automated manual transmission (AMT) provide the potential for improving the power and economic performance. However, due to the direct connection between the driving motor and the input shaft of the transmission, the higher moment of inertia at the input of AMT would lead to a poor shift quality. Based on the dynamic analysis of the engagement process of AMT without synchronizer, the dynamic model of the engagement process was established by using AMESim software. Through the analysis of the engagement process, it was concluded that the higher contact force and longer meshing duration under reverse contacting engagement condition is the main reason for the shift difficulty. In order to improve the shift quality, the influences of the sleeve teeth shape parameters of reverse contacting chamfer on the engagement process were analyzed and the simulation validation was performed. The simulation results showed that reducing the width and increasing the angle of the reverse contacting chamfer can effectively reduce the engagement duration and the contact force impulse, although the vehicle jerk was increased slightly, which did not exceed the most stringent criterion value of 10 m·s-3. Optimization of teeth shape parameters of reverse contacting chamfer can be considered to improve the shift quality of the electric vehicle equipped with an AMT.
{"title":"Influence of the Sleeve Teeth Shape Parameters on the Shifting Process of Automated Manual Transmission for Electric Vehicles","authors":"Bin Wu, Cun-Gin Chen","doi":"10.4271/14-09-02-0008","DOIUrl":"https://doi.org/10.4271/14-09-02-0008","url":null,"abstract":"Electric vehicles equipped with automated manual transmission (AMT) provide the potential for improving the power and economic performance. However, due to the direct connection between the driving motor and the input shaft of the transmission, the higher moment of inertia at the input of AMT would lead to a poor shift quality. Based on the dynamic analysis of the engagement process of AMT without synchronizer, the dynamic model of the engagement process was established by using AMESim software. Through the analysis of the engagement process, it was concluded that the higher contact force and longer meshing duration under reverse contacting engagement condition is the main reason for the shift difficulty. In order to improve the shift quality, the influences of the sleeve teeth shape parameters of reverse contacting chamfer on the engagement process were analyzed and the simulation validation was performed. The simulation results showed that reducing the width and increasing the angle of the reverse contacting chamfer can effectively reduce the engagement duration and the contact force impulse, although the vehicle jerk was increased slightly, which did not exceed the most stringent criterion value of 10 m·s-3. Optimization of teeth shape parameters of reverse contacting chamfer can be considered to improve the shift quality of the electric vehicle equipped with an AMT.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"50 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84767210","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}
SoDuk Lee, C. Fulper, D. Cullen, J. McDonald, Antonio Fernandez, M. Doorlag, L. J. Sanchez, Michael Olechiw
Portable emission measurement systems (PEMS) [1] are used by the US Environmental Protection Agency (EPA) to measure gaseous and particulate matter mass emissions from vehicles in normal, in-use, on-the-road, and “real-world” operations to support many of its programs. These programs include vehicle modeling, emissions compliance, regulatory development, emissions inventory development, and investigations of the effects of real, in-use driving conditions on NOx, CO2, and other regulated pollutants. This article discusses EPA’s analytical methodology for evaluating light-duty vehicle energy and EU Real Driving Emissions (RDE). A simple, data-driven model was developed and validated using measured PEMS emissions test data. The work also included application of the EU RDE procedures and comparison to the PEMS test methodologies and FTP and other chassis dynamometer test data used by EPA for characterizing in-use light- and heavy-duty vehicle emissions. This work was conducted as part of EPA’s participation in the development of UNECE Global Technical Regulations and also supports EPA mobile source emission inventory development. This article discusses the real-world emissions of light-duty vehicles with 12V Start-Stop technology and light-duty vehicles using both gasoline and diesel fuels.
{"title":"On-Road Portable Emission Measurement Systems Test Data Analysis and Light-Duty Vehicle In-Use Emissions Development","authors":"SoDuk Lee, C. Fulper, D. Cullen, J. McDonald, Antonio Fernandez, M. Doorlag, L. J. Sanchez, Michael Olechiw","doi":"10.4271/14-09-02-0007","DOIUrl":"https://doi.org/10.4271/14-09-02-0007","url":null,"abstract":"Portable emission measurement systems (PEMS) [1] are used by the US Environmental Protection Agency (EPA) to measure gaseous and particulate matter mass emissions from vehicles in normal, in-use, on-the-road, and “real-world” operations to support many of its programs. These programs include vehicle modeling, emissions compliance, regulatory development, emissions inventory development, and investigations of the effects of real, in-use driving conditions on NOx, CO2, and other regulated pollutants. This article discusses EPA’s analytical methodology for evaluating light-duty vehicle energy and EU Real Driving Emissions (RDE). A simple, data-driven model was developed and validated using measured PEMS emissions test data. The work also included application of the EU RDE procedures and comparison to the PEMS test methodologies and FTP and other chassis dynamometer test data used by EPA for characterizing in-use light- and heavy-duty vehicle emissions. This work was conducted as part of EPA’s participation in the development of UNECE Global Technical Regulations and also supports EPA mobile source emission inventory development. This article discusses the real-world emissions of light-duty vehicles with 12V Start-Stop technology and light-duty vehicles using both gasoline and diesel fuels.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"20 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78468105","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}
Aqueel Ahmad, M. S. Alam, Y. Rafat, S. Shariff, Ibrahim Alsaidan, R. Chabaan
Power pad designing, misalignment reduction, safety, automation, living object detection (LOD), and foreign object debris (FOD) detection are the key challenges in the commercialization of the high voltage wireless charging of Electric Vehicles (EV). The interruption from unwanted and sensitive foreign objects such as metal objects and living objects over the charging pads is an immense challenge for the static wireless charging of EV. In this manuscript, the problem of interference due to foreign objects and living objects has been analyzed, and an innovative laser- and sensor-based FOD detection method is proposed and verified by developing a prototype setup. Modeling and analysis of the effects of foreign objects have been performed using Finite Element Analysis (FEA) in Ansys Maxwell® environment. The analysis compares the consequence of the presence of foreign objects on the wireless charging power pad. The proposed method utilizes laser light and sensor for the detection and two-dimensional signal processing for the elimination of FOD. The proposed method is compatible with all types of static wireless charging systems without interrupting the power transfer and power circuit. The proposed system has been analyzed and compared with the various available FOD detection techniques. The feasibility of the proposed system has been assessed with the help of an on the bench hardware prototype implementation in the lab environment.
{"title":"Foreign Object Debris Detection and Automatic Elimination for Autonomous Electric Vehicles Wireless Charging Application","authors":"Aqueel Ahmad, M. S. Alam, Y. Rafat, S. Shariff, Ibrahim Alsaidan, R. Chabaan","doi":"10.4271/14-09-02-0006","DOIUrl":"https://doi.org/10.4271/14-09-02-0006","url":null,"abstract":"Power pad designing, misalignment reduction, safety, automation, living object detection (LOD), and foreign object debris (FOD) detection are the key challenges in the commercialization of the high voltage wireless charging of Electric Vehicles (EV). The interruption from unwanted and sensitive foreign objects such as metal objects and living objects over the charging pads is an immense challenge for the static wireless charging of EV. In this manuscript, the problem of interference due to foreign objects and living objects has been analyzed, and an innovative laser- and sensor-based FOD detection method is proposed and verified by developing a prototype setup. Modeling and analysis of the effects of foreign objects have been performed using Finite Element Analysis (FEA) in Ansys Maxwell® environment. The analysis compares the consequence of the presence of foreign objects on the wireless charging power pad. The proposed method utilizes laser light and sensor for the detection and two-dimensional signal processing for the elimination of FOD. The proposed method is compatible with all types of static wireless charging systems without interrupting the power transfer and power circuit. The proposed system has been analyzed and compared with the various available FOD detection techniques. The feasibility of the proposed system has been assessed with the help of an on the bench hardware prototype implementation in the lab environment.","PeriodicalId":36261,"journal":{"name":"SAE International Journal of Electrified Vehicles","volume":"115 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88099895","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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