Pub Date : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8994027
J. Tochtermann, Stephan Brandl
The need for zero emission transport solutions in urban areas is strongly driven by topics like local air pollution, noise emissions as well as global CO2 reduction and public pressure. One solution for this demand are battery electric vehicles with the focus to provide emission free urban transportation combined with lowest total cost of ownership and consequently a positive business case for the end customers. Requirements and approaches to achieve this important goal are discussed in this paper.
{"title":"Development of an Integrated Axle for MD Trucks for Urban Distribution Traffic","authors":"J. Tochtermann, Stephan Brandl","doi":"10.1109/ICEVT48285.2019.8994027","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8994027","url":null,"abstract":"The need for zero emission transport solutions in urban areas is strongly driven by topics like local air pollution, noise emissions as well as global CO2 reduction and public pressure. One solution for this demand are battery electric vehicles with the focus to provide emission free urban transportation combined with lowest total cost of ownership and consequently a positive business case for the end customers. Requirements and approaches to achieve this important goal are discussed in this paper.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116512023","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8993978
I. B. Mores, M. Fauzan, Y. Y. Nazaruddin, Parsaulian Ishaya Siregar
Particle Swarm Optimization (PSO) and Brain Storm Optimization (BSO) are alternative methods to find out the optimized solution of a non-linear equation. This paper will discuss the application of both methods to find out the weight of neurons from Adaptive Neuro Fuzzy Inference Systems (ANFIS) technique, which is used in predicting the bus arrival time at the bus stop. Comparison of the performance from both methods will also be made. After the modeling, training and testing of the proposed algorithm, the RMSE value produced from ANFIS which was trained by the PSO testing was 0.8145, and if it was trained by BSO was 0.8352. These results also conclude that the ANFIS with PSO algorithm yields better predicting bus arrival time better rather than ANFIS BSO in this case.
{"title":"Using Particle Swarm and Brain Storm Optimization for Predicting Bus Arrival Time","authors":"I. B. Mores, M. Fauzan, Y. Y. Nazaruddin, Parsaulian Ishaya Siregar","doi":"10.1109/ICEVT48285.2019.8993978","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8993978","url":null,"abstract":"Particle Swarm Optimization (PSO) and Brain Storm Optimization (BSO) are alternative methods to find out the optimized solution of a non-linear equation. This paper will discuss the application of both methods to find out the weight of neurons from Adaptive Neuro Fuzzy Inference Systems (ANFIS) technique, which is used in predicting the bus arrival time at the bus stop. Comparison of the performance from both methods will also be made. After the modeling, training and testing of the proposed algorithm, the RMSE value produced from ANFIS which was trained by the PSO testing was 0.8145, and if it was trained by BSO was 0.8352. These results also conclude that the ANFIS with PSO algorithm yields better predicting bus arrival time better rather than ANFIS BSO in this case.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"4044 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550081","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8993968
S. Sulistyo, A. M. Wibowo, Sri Nugroho
The development of photovoltaic has shown the maturity of technology. The application can already be used as a source of electrical energy and is an environmentally friendly source of electrical energy. The use of PV technology in Indonesia has developed well for the generation of electricity for companies or household units as an alternative energy source. Currently, Indonesia has begun to develop electric car transportation by using batteries, so that it was need inverter equipment which change a direct current to the alternating current. This paper discusses the comparison of power consumption 125 watts pump by using alternating current (AC) and direct current (DC) based on solar energy using photovoltaic (PV). The type PV cell uses a 100-watt peak solar cell type silicon mounted on a portable basis and parallel connected. The PV is installed at Semarang region which connected by battery. The type battery is 100 AH, 12 V. The battery was connected to motor pump of 125 watts. There are two motors type which has specification as DC motor and AC motor. The DC motor should be connected by DC-DC converter before DC motor pump to increase the requirement voltage of motor pump while AC motor should be provided by inverter DC to AC. The pump was connected by piping system which suction pipe use a diameter of 32 mm and discharge pipe of 20 mm. The total head for both experiment is 4 m. The speed of motor was measured as in motor specification. The operating of PV was at 08.00 am – 16.00 pm. The result of the power consumption of the DC motor was more efficiency than by using AC motor. The operation of the battery using DC motor is about two times longer than AC motor.
{"title":"Comparison Power Consumption 125 Watts Pump by Using AC and DC Based on Solar Energy","authors":"S. Sulistyo, A. M. Wibowo, Sri Nugroho","doi":"10.1109/ICEVT48285.2019.8993968","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8993968","url":null,"abstract":"The development of photovoltaic has shown the maturity of technology. The application can already be used as a source of electrical energy and is an environmentally friendly source of electrical energy. The use of PV technology in Indonesia has developed well for the generation of electricity for companies or household units as an alternative energy source. Currently, Indonesia has begun to develop electric car transportation by using batteries, so that it was need inverter equipment which change a direct current to the alternating current. This paper discusses the comparison of power consumption 125 watts pump by using alternating current (AC) and direct current (DC) based on solar energy using photovoltaic (PV). The type PV cell uses a 100-watt peak solar cell type silicon mounted on a portable basis and parallel connected. The PV is installed at Semarang region which connected by battery. The type battery is 100 AH, 12 V. The battery was connected to motor pump of 125 watts. There are two motors type which has specification as DC motor and AC motor. The DC motor should be connected by DC-DC converter before DC motor pump to increase the requirement voltage of motor pump while AC motor should be provided by inverter DC to AC. The pump was connected by piping system which suction pipe use a diameter of 32 mm and discharge pipe of 20 mm. The total head for both experiment is 4 m. The speed of motor was measured as in motor specification. The operating of PV was at 08.00 am – 16.00 pm. The result of the power consumption of the DC motor was more efficiency than by using AC motor. The operation of the battery using DC motor is about two times longer than AC motor.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121612582","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8994013
Muchamad Iman Karmawijaya, Irsyad Nashirul Haq, E. Leksono, A. Widyotriatmo
Electric Vehicle (EV) Batteries must have high reliability to produce durable and sustainable electrical energy. Reliable electric batteries will certainly have high economic value and efficiency. Reliability can be obtained if the system and its supporting are monitored using an integrated and independent system for further analysis and observation. Battery Management System (BMS) is integrated parts of Electric Vehicle, Hybrid Electric Vehicle (HEV), or solar applications e.g. solar power plant. Its functions are to integrate many things such as voltage sampling from cell battery, cells balancing, determine State of Charge (SOC), estimate State of Health (SOH), and predict Remaining Useful Life (RUL). The key technology needed for condition-based maintenance is Prognostic and Health Management. It is a new engineering approach that allows an assessment of the system's health when the system is operating. It combines various scientific disciplines, namely: sensing technology, modern statistics, machine learning, physics of failure, and reliability engineering. It will be combined with Big Data analysis. Big data uses existing technology and contemporary architecture that is designed to efficiently take advantage of the many and varied data. Big data analytics refers to the method of analyzing huge volumes of data, high velocity of data, variety different forms of data, and veracity of uncertainty of data. The main focus in this research is the development of an integrated observation system and the ability to make error predictions. This system consists of error detection, error diagnosis, and integrated prognosis. This research is to implement Big Data analytics Platform to evaluate the reliability level of electric vehicle Battery Management System.
{"title":"Development of Big Data Analytics Platform for Electric Vehicle Battery Management System","authors":"Muchamad Iman Karmawijaya, Irsyad Nashirul Haq, E. Leksono, A. Widyotriatmo","doi":"10.1109/ICEVT48285.2019.8994013","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8994013","url":null,"abstract":"Electric Vehicle (EV) Batteries must have high reliability to produce durable and sustainable electrical energy. Reliable electric batteries will certainly have high economic value and efficiency. Reliability can be obtained if the system and its supporting are monitored using an integrated and independent system for further analysis and observation. Battery Management System (BMS) is integrated parts of Electric Vehicle, Hybrid Electric Vehicle (HEV), or solar applications e.g. solar power plant. Its functions are to integrate many things such as voltage sampling from cell battery, cells balancing, determine State of Charge (SOC), estimate State of Health (SOH), and predict Remaining Useful Life (RUL). The key technology needed for condition-based maintenance is Prognostic and Health Management. It is a new engineering approach that allows an assessment of the system's health when the system is operating. It combines various scientific disciplines, namely: sensing technology, modern statistics, machine learning, physics of failure, and reliability engineering. It will be combined with Big Data analysis. Big data uses existing technology and contemporary architecture that is designed to efficiently take advantage of the many and varied data. Big data analytics refers to the method of analyzing huge volumes of data, high velocity of data, variety different forms of data, and veracity of uncertainty of data. The main focus in this research is the development of an integrated observation system and the ability to make error predictions. This system consists of error detection, error diagnosis, and integrated prognosis. This research is to implement Big Data analytics Platform to evaluate the reliability level of electric vehicle Battery Management System.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116950019","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8994031
Dani Irawan, S. Santosa, A. Jusuf, P. Sambegoro
The research in the electric vehicle requires a safe Reserved Energy Storage System (RESS) that is durable and crashworthy to withstand a harsh environment, especially ground impact from stone debris on the road. RESS, which typically uses lithium-ion type battery, is posed to the danger of thermal runaway as an aftermath of intrusion into the battery cell structures. Thermal runaway might happen because the separators between the anode and cathode damage and fail that result in a short circuit. Nowadays, metallic structures have been applied underneath the cells to protect RESS. However, the protection cannot hold high-speed impact properly. This research focuses on a composite-based protective layer by using sandwich panel constructions to achieve a stiffer structure. The design and analysis of the sandwich composite structure was conducted using non-linear finite element analysis. The study involves multiple design variables to take into account variations such as layer thickness, topology, and fiber orientation. This research only uses plain weave Carbon Fiber Reinforced Polymer (CFRP). The variables that are set as performance indicators are mainly cell deformation and energy absorbed. Among the two topologies tested, Navy Truss (NavTruss) model is proven to have better performance compared to the Blast Resistant Adaptive Sandwich (BRAS) model. This due to the NavTruss structure absorbs energy by undergoing progressive crushing, while BRAS structure collapse within the supports. In the NavTruss itself, various orientations are tested, and it is found that the most effective orientation is [(0/90)2/[(±45)/(0/90)]3]s. The optimum NavTruss composite structure configuration appears to be more superior with 36 percent mass saving compared to the metallic structure.
{"title":"Sandwich Panel Composite Based Light-Weight Structure Design for Reserved Energy Storage System (RESS) Protection","authors":"Dani Irawan, S. Santosa, A. Jusuf, P. Sambegoro","doi":"10.1109/ICEVT48285.2019.8994031","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8994031","url":null,"abstract":"The research in the electric vehicle requires a safe Reserved Energy Storage System (RESS) that is durable and crashworthy to withstand a harsh environment, especially ground impact from stone debris on the road. RESS, which typically uses lithium-ion type battery, is posed to the danger of thermal runaway as an aftermath of intrusion into the battery cell structures. Thermal runaway might happen because the separators between the anode and cathode damage and fail that result in a short circuit. Nowadays, metallic structures have been applied underneath the cells to protect RESS. However, the protection cannot hold high-speed impact properly. This research focuses on a composite-based protective layer by using sandwich panel constructions to achieve a stiffer structure. The design and analysis of the sandwich composite structure was conducted using non-linear finite element analysis. The study involves multiple design variables to take into account variations such as layer thickness, topology, and fiber orientation. This research only uses plain weave Carbon Fiber Reinforced Polymer (CFRP). The variables that are set as performance indicators are mainly cell deformation and energy absorbed. Among the two topologies tested, Navy Truss (NavTruss) model is proven to have better performance compared to the Blast Resistant Adaptive Sandwich (BRAS) model. This due to the NavTruss structure absorbs energy by undergoing progressive crushing, while BRAS structure collapse within the supports. In the NavTruss itself, various orientations are tested, and it is found that the most effective orientation is [(0/90)2/[(±45)/(0/90)]3]s. The optimum NavTruss composite structure configuration appears to be more superior with 36 percent mass saving compared to the metallic structure.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114130286","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 : 2019-11-01DOI: 10.1109/icevt48285.2019.8994023
{"title":"ICEVT 2019 TOC","authors":"","doi":"10.1109/icevt48285.2019.8994023","DOIUrl":"https://doi.org/10.1109/icevt48285.2019.8994023","url":null,"abstract":"","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125612000","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8993965
Christio Revano Mege, Irsyad Nashirul Haq, E. Leksono, F. Nugroho Soelami
In this research the discharging process to find the effect of temperature rising on prismatic lithium iron phosphate battery performances such as depth of discharge and electricity generation efficiency had been conducted. Battery discharging system has been built to acquire data such as temperature, voltage and electric current. Discharging temperature data were taken from single cell and module that consists of eight cells at three different C-rates which are 0.7C, 1.4C and 2.1C. After that discharging temperature data acquired from data acquisition process is used as training data and test data to predict temperature using Holt’s Double Exponential Smoothing. The results show that the depth of discharge of single cell and module were getting smaller as the C-rates increased. The same condition also occurred on electricity generation efficiency. The efficiencies were also getting smaller when the C-rates were getting larger. Temperature predictions conducted show that Holt’s Double Exponential Smoothing can nicely predict the temperature rising in single cell. In module temperature predictions, training data was taken from one cell only to predict the rest of the cells. At 0.7C, Holt methods can predict six out of eight cells well. Five out of eight cells could also be predicted well at 1.4C. However at 2.1C, just four cells could be predicted well. The predictions accuracy of Holt’s Double Exponential Smoothing decreased when the temperature uniformity in module decreased as the C-rate increased.
{"title":"Battery Discharging Temperature Prediction Using Holt’s Double Exponential Smoothing","authors":"Christio Revano Mege, Irsyad Nashirul Haq, E. Leksono, F. Nugroho Soelami","doi":"10.1109/ICEVT48285.2019.8993965","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8993965","url":null,"abstract":"In this research the discharging process to find the effect of temperature rising on prismatic lithium iron phosphate battery performances such as depth of discharge and electricity generation efficiency had been conducted. Battery discharging system has been built to acquire data such as temperature, voltage and electric current. Discharging temperature data were taken from single cell and module that consists of eight cells at three different C-rates which are 0.7C, 1.4C and 2.1C. After that discharging temperature data acquired from data acquisition process is used as training data and test data to predict temperature using Holt’s Double Exponential Smoothing. The results show that the depth of discharge of single cell and module were getting smaller as the C-rates increased. The same condition also occurred on electricity generation efficiency. The efficiencies were also getting smaller when the C-rates were getting larger. Temperature predictions conducted show that Holt’s Double Exponential Smoothing can nicely predict the temperature rising in single cell. In module temperature predictions, training data was taken from one cell only to predict the rest of the cells. At 0.7C, Holt methods can predict six out of eight cells well. Five out of eight cells could also be predicted well at 1.4C. However at 2.1C, just four cells could be predicted well. The predictions accuracy of Holt’s Double Exponential Smoothing decreased when the temperature uniformity in module decreased as the C-rate increased.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133065071","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8993974
T. Andromeda, I. Haryanto, J. Setiawan, Hermawan, B. Nugroho, Mohamad Isnaeni Romadhon, I. Setiawan, M. Facta, Abd Rahim Mat Sidek
Electric Vehicle (EV) cars have developed very rapidly. In line with a growing number on the streets, the need for electric vehicle battery charging stations is increasingly expected. In community, there are three levels of battery charging stations that have been implemented. Level 1 is a charger with a 120 Vac source and it is the slowest charger level. Level 2 is a familiar charger found in homes and garages use a 240 Vac source. While level 3 is a Direct Current Fast Charger (DCFC) charger which is urgently needed for electric vehicle (EV). This paper will present the results of research on charging a Lithium Iron Phosphate (LFP) battery using a DCFC buck converter. The converter is dedicated to be a charger of the EV. The result shows that the proposed converter has good performance because it has successfully charged the battery pack at 4 Ampere in the initial stage and it turned into full charge stage in 30 minutes at stable voltage at 14.4 Volt.
{"title":"Design of DC Fast Charging Buck Converter for LFP Battery on Electric Car","authors":"T. Andromeda, I. Haryanto, J. Setiawan, Hermawan, B. Nugroho, Mohamad Isnaeni Romadhon, I. Setiawan, M. Facta, Abd Rahim Mat Sidek","doi":"10.1109/ICEVT48285.2019.8993974","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8993974","url":null,"abstract":"Electric Vehicle (EV) cars have developed very rapidly. In line with a growing number on the streets, the need for electric vehicle battery charging stations is increasingly expected. In community, there are three levels of battery charging stations that have been implemented. Level 1 is a charger with a 120 Vac source and it is the slowest charger level. Level 2 is a familiar charger found in homes and garages use a 240 Vac source. While level 3 is a Direct Current Fast Charger (DCFC) charger which is urgently needed for electric vehicle (EV). This paper will present the results of research on charging a Lithium Iron Phosphate (LFP) battery using a DCFC buck converter. The converter is dedicated to be a charger of the EV. The result shows that the proposed converter has good performance because it has successfully charged the battery pack at 4 Ampere in the initial stage and it turned into full charge stage in 30 minutes at stable voltage at 14.4 Volt.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133670905","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 : 2019-11-01DOI: 10.1109/ICEVT48285.2019.8994022
G. D. Haryadi, Septian N. I. Pramaishella, I. Haryanto, S. Santosa
The number of motor vehicle increases at each year in Indonesia involve much negative impact on human life such as traffic jam. People choose to go by bus to avoid the traffic jam. Another negative impact is an increase amount of carbon dioxide (CO2) emissions in the air. Replacing motor vehicle to electric vehicle is the better way to decrease amount of carbon dioxide emissions. Range extended electric bus is a type of electric bus which use electric and fuel for energy source. On the basis of a typical Japanese driving cycle, optimal control strategy is designed according to the state of charge (SOC) consumption trend, which is optimized by the dynamic programming (DP) algorithm. The SOC value determines the mileage and fuel consumption, it will be the main goal of energy management. The result show that when REEB go through distance as long as the distance of BRT UNDIP – UNNES bus route, the amount of Japanese driving cycle are 11 cycles. The energy and fuel consumption that optimized by DP strategy can reach 121.66 MJ and 0.0143 L/Km. Compared with the conventional bus, the fuel consumption reach 0.212 L/Km.
{"title":"Modelling and Optimization of Energy Range Extended Electric Bus Strategy Management System Using Dynamic Programming","authors":"G. D. Haryadi, Septian N. I. Pramaishella, I. Haryanto, S. Santosa","doi":"10.1109/ICEVT48285.2019.8994022","DOIUrl":"https://doi.org/10.1109/ICEVT48285.2019.8994022","url":null,"abstract":"The number of motor vehicle increases at each year in Indonesia involve much negative impact on human life such as traffic jam. People choose to go by bus to avoid the traffic jam. Another negative impact is an increase amount of carbon dioxide (CO2) emissions in the air. Replacing motor vehicle to electric vehicle is the better way to decrease amount of carbon dioxide emissions. Range extended electric bus is a type of electric bus which use electric and fuel for energy source. On the basis of a typical Japanese driving cycle, optimal control strategy is designed according to the state of charge (SOC) consumption trend, which is optimized by the dynamic programming (DP) algorithm. The SOC value determines the mileage and fuel consumption, it will be the main goal of energy management. The result show that when REEB go through distance as long as the distance of BRT UNDIP – UNNES bus route, the amount of Japanese driving cycle are 11 cycles. The energy and fuel consumption that optimized by DP strategy can reach 121.66 MJ and 0.0143 L/Km. Compared with the conventional bus, the fuel consumption reach 0.212 L/Km.","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130083863","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 : 2019-11-01DOI: 10.1109/icevt48285.2019.8993862
{"title":"ICEVT 2019 Program Book","authors":"","doi":"10.1109/icevt48285.2019.8993862","DOIUrl":"https://doi.org/10.1109/icevt48285.2019.8993862","url":null,"abstract":"","PeriodicalId":125935,"journal":{"name":"2019 6th International Conference on Electric Vehicular Technology (ICEVT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123514252","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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