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Papers by Madhavi Nerkar
International Journal for Research in Applied Science and Engineering Technology
: The main requirement for the adoption and implementation of electric vehicles (EV) is the avail... more : The main requirement for the adoption and implementation of electric vehicles (EV) is the availability of charging facilities in public locations. In order to create an enabling EVSE ecosystem and hasten the adoption of EVs, this paper addresses several challenges relating to electric vehicle supply equipment (EVSE) or charging stations linked to legislation, standards, interoperability, and business models. Electric vehicle (EV) supply equipment (EVSE) or charging equipment are necessary for vehicle owners to adopt EVs. With varying degrees of success, several nations utilised various strategies and economic models to build the EVSE ecosystem. As India prepares to launch an EV revolution, a few crucial EVSE-related questions continue to plague the industry's players: What criteria apply to EVSE in India? whose will berun and keep up an EVSE? Utilities? Utility franchisees, perhaps? or outside parties like business owners, parking lot managers, and fleet operators? What will the electricity cost be for charging an EV? Will there be only energy charges or will there be capacity charges as well (minimum monthly fee per kW of capacity)? Who will cover the expense of the electric grid upgrade (higher capacity distribution transformers and new cables when necessary): the owner of the EVSE or the utility's usual grid improvement capex? Where will the public EVSEs be installed, and will the land be given away for free, at a discount, or at market value? This paper seeks to summarise the extensive work that has previously been done by numerous parties on the aforementioned topics and environment that will facilitate the rapid implementation of EVs.
INTERNATIONAL CONFERENCE ON TRENDS IN CHEMICAL ENGINEERING 2021 (ICoTRiCE2021)
Electric vehicles (EVs) are being introduced by various manufacturers as an environment-friendly ... more Electric vehicles (EVs) are being introduced by various manufacturers as an environment-friendly alternative to vehicles with internal combustion engines and with some advantages. The quantity of EVs will grow quickly in the coming years. However, the uncoordinated charging of these vehicles can put extreme stress on the power grid. The problem of charge scheduling of EVs is significant and challenging and also has seen significant research over the most recent couple of years. This survey covers the new works done in the area of scheduling algorithms for charging EVs in smart grids. Some heuristic and meta-heuristic algorithm are considered for the real-time charging. EV scheduling method by Genetic Algorithm and Intelligent Scatter Search (ISS) algorithm (GA and ISS), Particle Swarm Optimization (PSO) algorithm, and Reinforcement Learning algorithm(RL) are developed for power loss minimization, electricity cost minimization, peak load reduction. In this point of view interested to propose to integrate fog computing with RL applications deployment in EV charging distributed systems. This integration between fog computing and the RL may have the opportunity to shape the future applications established in the EV charging systems.
Nowadays, reactive power control has been playing a vital role in a systematic study of maintaini... more Nowadays, reactive power control has been playing a vital role in a systematic study of maintaining a secure voltage limit in the transmission system. When large inductive loads are connected in the transmission line then the matter of poor power factor is faced because of lagging load current. Sometimes, due to a small load, very low current flows through transmission line causing in a leading shunt capacitance in transmission line result increase in voltage to the receiving end voltage may become twice of the sending end voltage (Ferranti effect), in a long transmission line. To minimize these issues we are using a parallel combination of thyristor switched capacitor (TSC) and thyristor controlled reactor (TCR). The microcontroller/Arduino is used to vary the firing angle of thyristor then we get smooth current control range from capacitive to inductive value. This paper shows the study of FACTS devices (TSC-TCR) which are used to control reactive power n electrical power system t...
Accurate estimation of parameters during transient and steady state is required for controlling o... more Accurate estimation of parameters during transient and steady state is required for controlling of Induction motor. Artificial neural networks (ANNs) based online identification of induction motor parameters are presented. ANNs such as feed forward network is used to develop an ANN as a memory for remembering the estimated parameters and for computing the parameters during transients. Simulations and experimental results are presented for induction motors. The Induction motor is a nonlinear multivariable dynamic system with parameters that vary with temperature, frequency, saturation, and operating point. Considering that induction motors are widely used in industrial applications, these parameters have a significant effect on the accuracy and efficiency of the motors and, ultimately, the overall system performance. Therefore, it is essential to develop algorithms for online parameter estimation of the induction motor. Such algorithms can be performed in real time because of the pro...
battery thermal management system by Madhavi Nerkar
International Journal for Research in Applied Science and Engineering Technology
: The main requirement for the adoption and implementation of electric vehicles (EV) is the avail... more : The main requirement for the adoption and implementation of electric vehicles (EV) is the availability of charging facilities in public locations. In order to create an enabling EVSE ecosystem and hasten the adoption of EVs, this paper addresses several challenges relating to electric vehicle supply equipment (EVSE) or charging stations linked to legislation, standards, interoperability, and business models. Electric vehicle (EV) supply equipment (EVSE) or charging equipment are necessary for vehicle owners to adopt EVs. With varying degrees of success, several nations utilised various strategies and economic models to build the EVSE ecosystem. As India prepares to launch an EV revolution, a few crucial EVSE-related questions continue to plague the industry's players: What criteria apply to EVSE in India? whose will berun and keep up an EVSE? Utilities? Utility franchisees, perhaps? or outside parties like business owners, parking lot managers, and fleet operators? What will the electricity cost be for charging an EV? Will there be only energy charges or will there be capacity charges as well (minimum monthly fee per kW of capacity)? Who will cover the expense of the electric grid upgrade (higher capacity distribution transformers and new cables when necessary): the owner of the EVSE or the utility's usual grid improvement capex? Where will the public EVSEs be installed, and will the land be given away for free, at a discount, or at market value? This paper seeks to summarise the extensive work that has previously been done by numerous parties on the aforementioned topics and environment that will facilitate the rapid implementation of EVs.
INTERNATIONAL CONFERENCE ON TRENDS IN CHEMICAL ENGINEERING 2021 (ICoTRiCE2021)
Electric vehicles (EVs) are being introduced by various manufacturers as an environment-friendly ... more Electric vehicles (EVs) are being introduced by various manufacturers as an environment-friendly alternative to vehicles with internal combustion engines and with some advantages. The quantity of EVs will grow quickly in the coming years. However, the uncoordinated charging of these vehicles can put extreme stress on the power grid. The problem of charge scheduling of EVs is significant and challenging and also has seen significant research over the most recent couple of years. This survey covers the new works done in the area of scheduling algorithms for charging EVs in smart grids. Some heuristic and meta-heuristic algorithm are considered for the real-time charging. EV scheduling method by Genetic Algorithm and Intelligent Scatter Search (ISS) algorithm (GA and ISS), Particle Swarm Optimization (PSO) algorithm, and Reinforcement Learning algorithm(RL) are developed for power loss minimization, electricity cost minimization, peak load reduction. In this point of view interested to propose to integrate fog computing with RL applications deployment in EV charging distributed systems. This integration between fog computing and the RL may have the opportunity to shape the future applications established in the EV charging systems.
Nowadays, reactive power control has been playing a vital role in a systematic study of maintaini... more Nowadays, reactive power control has been playing a vital role in a systematic study of maintaining a secure voltage limit in the transmission system. When large inductive loads are connected in the transmission line then the matter of poor power factor is faced because of lagging load current. Sometimes, due to a small load, very low current flows through transmission line causing in a leading shunt capacitance in transmission line result increase in voltage to the receiving end voltage may become twice of the sending end voltage (Ferranti effect), in a long transmission line. To minimize these issues we are using a parallel combination of thyristor switched capacitor (TSC) and thyristor controlled reactor (TCR). The microcontroller/Arduino is used to vary the firing angle of thyristor then we get smooth current control range from capacitive to inductive value. This paper shows the study of FACTS devices (TSC-TCR) which are used to control reactive power n electrical power system t...
Accurate estimation of parameters during transient and steady state is required for controlling o... more Accurate estimation of parameters during transient and steady state is required for controlling of Induction motor. Artificial neural networks (ANNs) based online identification of induction motor parameters are presented. ANNs such as feed forward network is used to develop an ANN as a memory for remembering the estimated parameters and for computing the parameters during transients. Simulations and experimental results are presented for induction motors. The Induction motor is a nonlinear multivariable dynamic system with parameters that vary with temperature, frequency, saturation, and operating point. Considering that induction motors are widely used in industrial applications, these parameters have a significant effect on the accuracy and efficiency of the motors and, ultimately, the overall system performance. Therefore, it is essential to develop algorithms for online parameter estimation of the induction motor. Such algorithms can be performed in real time because of the pro...