Pub Date : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333714
Arvind Kumar, Vikas Bhalla, Praveen Kumar
The evolution in transportation has been boosting the growth of societies and industry. The power plant and transportation sector are our planet's main sources of greenhouse gas emissions. The main aim of this article, can reduce emissions from the power and transportation sector. Vehicles are essential in daily transportation, and an increasing effort is being done to replace the pollutant combustion engines by plug-in hybrid electric vehicles (PHEVs). Better utilization of such potential depends on the optimal scheduling of charging and discharging PHEVs. Therefore, charging and discharging of PHEVs must be scheduled intelligently to prevent overloading of the network at peak hours, take advantages of off peak charging benefits and delaying any load shedding. In this paper presents a novel approach for solve the unit commitment problem of thermal units integrated with PHEVs in an electrical power system. An IEEE 10-unit test system is employed to investigate the impacts of PHEVs on generation scheduling and cost-emission. The results obtained from simulation analysis show a significant techno-economic saving.
{"title":"Unit commitment in a smart grid with plug-in hybrid electric vehicles — A cost-emission optimization","authors":"Arvind Kumar, Vikas Bhalla, Praveen Kumar","doi":"10.1109/ITEC-INDIA.2017.8333714","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333714","url":null,"abstract":"The evolution in transportation has been boosting the growth of societies and industry. The power plant and transportation sector are our planet's main sources of greenhouse gas emissions. The main aim of this article, can reduce emissions from the power and transportation sector. Vehicles are essential in daily transportation, and an increasing effort is being done to replace the pollutant combustion engines by plug-in hybrid electric vehicles (PHEVs). Better utilization of such potential depends on the optimal scheduling of charging and discharging PHEVs. Therefore, charging and discharging of PHEVs must be scheduled intelligently to prevent overloading of the network at peak hours, take advantages of off peak charging benefits and delaying any load shedding. In this paper presents a novel approach for solve the unit commitment problem of thermal units integrated with PHEVs in an electrical power system. An IEEE 10-unit test system is employed to investigate the impacts of PHEVs on generation scheduling and cost-emission. The results obtained from simulation analysis show a significant techno-economic saving.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130306141","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}
Automotive components and systems during their real world use face different types of drivers, different traffic condition and different road terrains. It is possible to map the vehicle use using GPS (Global Positioning Systems) systems, but it would result in huge pile of data with maps and pose difficulty in terrain mapping, adding to the challenges. Depending on the traffic situation drivers may behave differently on the mapped road sections. Adding technologies and hardware to enable vehicles determine their surrounding environment and react accordingly increases the cost of system. For smart and interconnected vehicle applications, with increased mechatronics and connectivity, determination of the road-type and driver type on the fly helps for optimizing strategies and performance. An algorithm that determines the type of road, using the data available from existing hardware, on which the vehicle is being driven — city, rural, highway, or suburban — and the type of driver — aggressive, economical, or normal — is being developed at Schaeffler. The algorithm also determines and constantly updates the real world duty cycles for different parts of the world. This helps in development and validation of systems for their actual usage.
{"title":"Smart mobility: Algorithm for road and driver type determination","authors":"Pritesh Doshi, Dheeraj Kapur, Ramkumar Iyer, Arkajyoti Chatterjee","doi":"10.1109/ITEC-INDIA.2017.8333895","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333895","url":null,"abstract":"Automotive components and systems during their real world use face different types of drivers, different traffic condition and different road terrains. It is possible to map the vehicle use using GPS (Global Positioning Systems) systems, but it would result in huge pile of data with maps and pose difficulty in terrain mapping, adding to the challenges. Depending on the traffic situation drivers may behave differently on the mapped road sections. Adding technologies and hardware to enable vehicles determine their surrounding environment and react accordingly increases the cost of system. For smart and interconnected vehicle applications, with increased mechatronics and connectivity, determination of the road-type and driver type on the fly helps for optimizing strategies and performance. An algorithm that determines the type of road, using the data available from existing hardware, on which the vehicle is being driven — city, rural, highway, or suburban — and the type of driver — aggressive, economical, or normal — is being developed at Schaeffler. The algorithm also determines and constantly updates the real world duty cycles for different parts of the world. This helps in development and validation of systems for their actual usage.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127801188","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333828
A. Veeraraghavan, Ajinkya Bhave, V. Adithya, Yasunori Yokojima, Shingo Harada, S. Komori, Yasuhide Yano
Fuel consumption in a Hybrid Electric Vehicle (HEV) is typically impacted by powertrain operation modes, short- and long-term driving trend and style, and road type and traffic conditions. Typically, HEVs have rule-based supervisory control using heuristic logic. This approach works sub-optimally because it does not have knowledge of either road conditions or driving trends. We propose a machine learning approach to enhance the HEV controller performance. We create a Driving Scene Recognizer (DSR) that uses the contextual information available to recognize the current driving scenario. This information would be used by the supervisory controller to decide the optimal vehicle commands at each instant of the drive cycle. A hierarchical deep learning network is trained on videos of driving data and vehicle sensor data to classify typical driving scenarios. We demonstrate the performance of the DSR on real-world test data.
{"title":"Driving scenario recognition for advanced hybrid electric vehicle control","authors":"A. Veeraraghavan, Ajinkya Bhave, V. Adithya, Yasunori Yokojima, Shingo Harada, S. Komori, Yasuhide Yano","doi":"10.1109/ITEC-INDIA.2017.8333828","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333828","url":null,"abstract":"Fuel consumption in a Hybrid Electric Vehicle (HEV) is typically impacted by powertrain operation modes, short- and long-term driving trend and style, and road type and traffic conditions. Typically, HEVs have rule-based supervisory control using heuristic logic. This approach works sub-optimally because it does not have knowledge of either road conditions or driving trends. We propose a machine learning approach to enhance the HEV controller performance. We create a Driving Scene Recognizer (DSR) that uses the contextual information available to recognize the current driving scenario. This information would be used by the supervisory controller to decide the optimal vehicle commands at each instant of the drive cycle. A hierarchical deep learning network is trained on videos of driving data and vehicle sensor data to classify typical driving scenarios. We demonstrate the performance of the DSR on real-world test data.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124373951","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333829
T. Maji, P. Acharjee
The utilization of phasor measurement unit (PMU) is highly recognized in modern power industry for its smart measurement capability. To implement a smart transmission network, PMU should be allocated at all buses but for large power systems, PMU allocation at all buses is a matter of huge investment and it should be conducted in certain number of steps. In this paper, an effective and practical multi-step PMU allocation strategy is proposed for IEEE 30-bus test system. In, the proposed strategy, the multi-step PMU allocation is framed in such a way that the important and preferred buses will be directly monitored during the initial and intermediate steps. In this paper, several strategies such as optimal PMU allocation (OPA) for full observability, important and critical bus preferences are taken into account. An efficient binary crow search algorithm (BCSA) is developed to solve the OPA problem and the developed algorithm is compared with other metaheuristic algorithms to show its efficiency.
{"title":"A strategic multi-step PMU allocation based on direct monitoring for smart grid (SG) implementation","authors":"T. Maji, P. Acharjee","doi":"10.1109/ITEC-INDIA.2017.8333829","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333829","url":null,"abstract":"The utilization of phasor measurement unit (PMU) is highly recognized in modern power industry for its smart measurement capability. To implement a smart transmission network, PMU should be allocated at all buses but for large power systems, PMU allocation at all buses is a matter of huge investment and it should be conducted in certain number of steps. In this paper, an effective and practical multi-step PMU allocation strategy is proposed for IEEE 30-bus test system. In, the proposed strategy, the multi-step PMU allocation is framed in such a way that the important and preferred buses will be directly monitored during the initial and intermediate steps. In this paper, several strategies such as optimal PMU allocation (OPA) for full observability, important and critical bus preferences are taken into account. An efficient binary crow search algorithm (BCSA) is developed to solve the OPA problem and the developed algorithm is compared with other metaheuristic algorithms to show its efficiency.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124482604","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8356946
Vishu Gupta, R. Kumar, Srikanth Reddy K, B. Panigrahi
Electric Vehicles (EVs) offer a solution to the growing emissions that are released due to internal combustion engine (ICE) based transportation. With the increase in the number of EVs on the road, charging infrastructure and management have to be accommodated for increased use of EVs. In this article, an EV cancellation event classification framework is proposed for a multi-aggregator EV charge scheduling scheme. Four cancellation motivations are detailed and corresponding impacts are observed on the aggregator profits. Further, the impact of rescheduling of cancelled slots on total profits is also explored. The profits including cancellation charges along with rescheduling of slots were the highest when compared with no rescheduling and no cancellation charges. In this work, less than 1% cancellations of the total scheduled vehicles are considered.
{"title":"Electric vehicle (EV) cancellation event classification for multi-aggregator EV charge scheduling (EVCS)","authors":"Vishu Gupta, R. Kumar, Srikanth Reddy K, B. Panigrahi","doi":"10.1109/ITEC-INDIA.2017.8356946","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8356946","url":null,"abstract":"Electric Vehicles (EVs) offer a solution to the growing emissions that are released due to internal combustion engine (ICE) based transportation. With the increase in the number of EVs on the road, charging infrastructure and management have to be accommodated for increased use of EVs. In this article, an EV cancellation event classification framework is proposed for a multi-aggregator EV charge scheduling scheme. Four cancellation motivations are detailed and corresponding impacts are observed on the aggregator profits. Further, the impact of rescheduling of cancelled slots on total profits is also explored. The profits including cancellation charges along with rescheduling of slots were the highest when compared with no rescheduling and no cancellation charges. In this work, less than 1% cancellations of the total scheduled vehicles are considered.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131376730","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333865
A. K. Birudula, A. K. Kesavarapu, T. Chelliah, D. Khare, U. Ramesh
Mostly tugboats are powered by diesel-electric generators for meeting power of auxiliary loads and of electric motors for propulsive load. This paper proposes the optimal fuel management in diesel-electric generators considering doubly fed asynchronous machine (DFAM) as generator. An optimization problem is formulated to schedule the available power sources aiming for best possible fuel efficiency. The performance of optimal control strategies critically depends on future load applied in generator. Considering this for predicting tugboat load demand a simple predictive methodology is proposed based on the average mode time per cycle. The proposed control mechanism is able to respond to any sudden load change and also to emergency halt condition. DFAM as generator is considered for improving the system efficiency at low load region. Speed of the diesel engine is decided by the load demand. Output voltage and frequency of DFAM at variable speeds are regulated by power electronic convertors, connected in rotor circuit.
{"title":"Optimization with load prediction in asynchronous generator driven tugboat propulsion system","authors":"A. K. Birudula, A. K. Kesavarapu, T. Chelliah, D. Khare, U. Ramesh","doi":"10.1109/ITEC-INDIA.2017.8333865","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333865","url":null,"abstract":"Mostly tugboats are powered by diesel-electric generators for meeting power of auxiliary loads and of electric motors for propulsive load. This paper proposes the optimal fuel management in diesel-electric generators considering doubly fed asynchronous machine (DFAM) as generator. An optimization problem is formulated to schedule the available power sources aiming for best possible fuel efficiency. The performance of optimal control strategies critically depends on future load applied in generator. Considering this for predicting tugboat load demand a simple predictive methodology is proposed based on the average mode time per cycle. The proposed control mechanism is able to respond to any sudden load change and also to emergency halt condition. DFAM as generator is considered for improving the system efficiency at low load region. Speed of the diesel engine is decided by the load demand. Output voltage and frequency of DFAM at variable speeds are regulated by power electronic convertors, connected in rotor circuit.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125410688","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333899
K. Sarrafan, D. Sutanto, K. Muttaqi
Battery modeling plays a crucial role in improving the performance of battery powered systems especially in electric vehicle (EV) applications. To date, many state-of-the-art battery models have been proposed by researchers to improve the performance of electric vehicles. In this paper, an electric circuit based approach for electric vehicle battery model capable of capturing dynamic capacity rate effects for runtime prediction, state of charge tracking and I-V performance is proposed. To compare the results, two well-known electrical circuit based battery models are accurately modeled in MATLAB Simulink and the accuracy and the simplicity of each model are then compared with the proposed model in this paper with the emphasis on rate capacity effects for state of charge tracking and runtime prediction. To extract the battery parameters and to verify the results of each battery model, experimental tests have also been conducted on four Li-ion LGHG2 3 Ah battery cells connected in series.
{"title":"An electric circuit based EV battery model for runtime prediction and state of charge tracking","authors":"K. Sarrafan, D. Sutanto, K. Muttaqi","doi":"10.1109/ITEC-INDIA.2017.8333899","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333899","url":null,"abstract":"Battery modeling plays a crucial role in improving the performance of battery powered systems especially in electric vehicle (EV) applications. To date, many state-of-the-art battery models have been proposed by researchers to improve the performance of electric vehicles. In this paper, an electric circuit based approach for electric vehicle battery model capable of capturing dynamic capacity rate effects for runtime prediction, state of charge tracking and I-V performance is proposed. To compare the results, two well-known electrical circuit based battery models are accurately modeled in MATLAB Simulink and the accuracy and the simplicity of each model are then compared with the proposed model in this paper with the emphasis on rate capacity effects for state of charge tracking and runtime prediction. To extract the battery parameters and to verify the results of each battery model, experimental tests have also been conducted on four Li-ion LGHG2 3 Ah battery cells connected in series.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114654080","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333832
Robindro Lairenlakpam, G. D. Thakre, Poonam Gupta, Y. Singh, Praveen Kumar
This paper presents a study that aims to determine the effect of different drive modes (acceleration, deceleration, cruising) on the energy consumption (EC) of an electric auto rickshaw (e-rickshaw). The performance tests for the e-rickshaw were conducted on-road as well as on chassis dynamometer which followed a new drive cycle. Drive cycle analysis was done to analyse the EC during vehicle operation and the drive modes. The study indicated that average EC of the e-rickshaw was 31.17 Wh/km for the cycle. The percentage contribution of the drive modes to input power, torque and output power were estimated using a computer program developed for the study and results presented.
{"title":"Effect of different drive modes on energy consumption of an electric auto rickshaw","authors":"Robindro Lairenlakpam, G. D. Thakre, Poonam Gupta, Y. Singh, Praveen Kumar","doi":"10.1109/ITEC-INDIA.2017.8333832","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333832","url":null,"abstract":"This paper presents a study that aims to determine the effect of different drive modes (acceleration, deceleration, cruising) on the energy consumption (EC) of an electric auto rickshaw (e-rickshaw). The performance tests for the e-rickshaw were conducted on-road as well as on chassis dynamometer which followed a new drive cycle. Drive cycle analysis was done to analyse the EC during vehicle operation and the drive modes. The study indicated that average EC of the e-rickshaw was 31.17 Wh/km for the cycle. The percentage contribution of the drive modes to input power, torque and output power were estimated using a computer program developed for the study and results presented.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116819572","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333840
R. Mallik, D. Venkatramanan, A. Adapa, V. John
This paper presents a resistance emulation based fault ride through scheme for standalone voltage source inverters. Typically, fast electronic protection schemes such as overcurrent and IGBT desaturation, are employed to detect inverter overload and short-circuit faults. However, this results in complete inverter shut-down rapidly, much before the slower electromechanical protection systems such as circuit breakers can function. In this work, a resistance emulation based technique is suggested that provides fault ride-through capability to the inverter, thus allowing electromechanical protections to function. A state machine is presented which incorporates hierarchal loop stability and multiple current constraints for appropriate impedance selection. The proposed method is verified in hardware.
{"title":"Resistance emulation based fault ride-through in standalone voltage source inverters","authors":"R. Mallik, D. Venkatramanan, A. Adapa, V. John","doi":"10.1109/ITEC-INDIA.2017.8333840","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333840","url":null,"abstract":"This paper presents a resistance emulation based fault ride through scheme for standalone voltage source inverters. Typically, fast electronic protection schemes such as overcurrent and IGBT desaturation, are employed to detect inverter overload and short-circuit faults. However, this results in complete inverter shut-down rapidly, much before the slower electromechanical protection systems such as circuit breakers can function. In this work, a resistance emulation based technique is suggested that provides fault ride-through capability to the inverter, thus allowing electromechanical protections to function. A state machine is presented which incorporates hierarchal loop stability and multiple current constraints for appropriate impedance selection. The proposed method is verified in hardware.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091355","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 : 2017-12-01DOI: 10.1109/ITEC-INDIA.2017.8333851
S. K. Giri, S. Mukherjee, Sourabh Kundu, Subrata Banerjee
A pulse width modulation (PWM) strategy for operation of three-level neutral-point-clamped (NPC) inverter in the full modulation range including overmodulation region with dc-link capacitor unbalance control is proposed. The overmodulation signals are derived in a simple and generalized way by properly adding a bias signal with the zero sequence injected modulation signals. It has been shown that the incorporation of a signal compression factor creates a room for addition of a compensating offset signal of appropriate polarity which can be used to generate neutral current in the right direction to mitigate prior unbalance in two dc-link capacitor voltages in the overmodulation region. A detailed study of the PWM algorithm for operation in both undermodulation and overmodulation region with capacitor voltage balancing strategy is carried out. The performances of the proposed scheme is evaluated through simulation and validated in experiments using a prototype three-level NPC inverter.
{"title":"An altered PWM strategy for overmodulation operation of three-level NPC inverter with capacitor voltage balancing","authors":"S. K. Giri, S. Mukherjee, Sourabh Kundu, Subrata Banerjee","doi":"10.1109/ITEC-INDIA.2017.8333851","DOIUrl":"https://doi.org/10.1109/ITEC-INDIA.2017.8333851","url":null,"abstract":"A pulse width modulation (PWM) strategy for operation of three-level neutral-point-clamped (NPC) inverter in the full modulation range including overmodulation region with dc-link capacitor unbalance control is proposed. The overmodulation signals are derived in a simple and generalized way by properly adding a bias signal with the zero sequence injected modulation signals. It has been shown that the incorporation of a signal compression factor creates a room for addition of a compensating offset signal of appropriate polarity which can be used to generate neutral current in the right direction to mitigate prior unbalance in two dc-link capacitor voltages in the overmodulation region. A detailed study of the PWM algorithm for operation in both undermodulation and overmodulation region with capacitor voltage balancing strategy is carried out. The performances of the proposed scheme is evaluated through simulation and validated in experiments using a prototype three-level NPC inverter.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122857414","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：