Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids
Abstract
:1. Introduction
- The impacts of selection of charging stations, sizing of the charging systems, and selection of sources. The different sources connected should ensure a suitable charging system, made with different technologies like on-board and off-board chargers. Suitable charging station architecture and selection of sources will reduce costs, dimensions, weights, and power rating, among other factors.
- Charging stations require standards to connect charging cords, cables, and connectors. The implementation of charging stations with standards can maximize the utilization of charging stations.
- The cost and performance of a charger depends on the semiconducting devices and its arrangement. All of this impacts one’s choice, and the size of the charging system is based on the converter topology used for conversion and gain of the corresponding converter.
- A charging station with renewable energy reduces the demand in the existing grid system and reduces fossil fuel-based conversion of energy. In addition, the effective use of renewable sources and utilization of sources through energy management increases usage of the EV.
2. Architecture of Multi-Point EV Charging Stations
2.1. Isolated DC Microgrid for EV Charging
Isolated DC Microgrid Control Strategy
2.2. Grid-Connected, RES-Powered DC MG for EV Charging
2.3. RES-Powered DC Microgrid with Direct Connection of ESU
Modes of Operation and Control Algorithm
2.4. AC Bus Coupled Charging Station Architecture
AC Bus-Connected Charging and Discharging Control
2.5. Hybrid AC-DC Microgrid
2.5.1. AC and DC Charging Station and Its Control
2.5.2. Frequency Droop Control
2.5.3. Angle Droop Control
2.5.4. Communication-Based Control
2.6. Multiport Converter with DC Grid Interconnection
2.7. Multiport Converter with AC Grid Interconnection
3. Charging Station Standards and Levels
4. EV Charging Connectors
5. Power Electronic Converters for Charging Stations
5.1. DC-DC Converters
5.2. AC-DC Converters
6. Control Strategy of Charging Stations
6.1. Rule-Based Control
6.2. Fuzzy Logic Control of Charging Stations
7. Energy Management in DC Microgrid-Based Charging Stations
- ➢
- Development of an energy management strategy to control the power flow among available sources and charging terminals for effective utilization of the generated renewable power.
- ➢
- In a PV-powered charging station, the power produced by the PV is variable in nature and it creates a DC bus voltage variation in the microgrid, irrespective of overloading and irradiation on the PV.
- ➢
- The charging port with the closed loop control provides constant current and constant voltage charging, and reduces charging time.
7.1. Microgrid-Connected EV Charging Stations
7.1.1. Energy Management Modes
7.1.2. Experimental Implementation
- Mode 1: ESU and PV to EV charging (PPV ≤ 120 W).
- Mode 2: Particular EV charging by PV (PPV ≤ 120 W).
- Mode 3: Utility grid and PV-based ESU charging (PPV ≤ 120 W).
- Mode 4: Utility grid and PV-connected EV charging (PPV ≤ 120 W).
- Mode 5: Utility grid and PV-powered EV and ESU charging (120 W ≤ PPV ≤ 160 w)
- Mode 6: PV-powered EV charging (120 W ≤ PPV ≤ 160 W).
- Mode 7: Utility grid powering (120 W ≤ PPV ≤ 160 W).
- Mode 8: PV-powered EV and ESU charging (160 W ≤ PPV ≤ 230 W).
- Mode 9: PV-powered energy storage (PPV ≥ 230 W).
- Mode 10: Energy storage to EV charging (PPV < PPV MIN).
- Mode 11: EV to EV (V2V) charging (PPV < PPV MIN).
- 1.
- Mode 2: Particular EV Charging by PV (PPV ≤ 120 W)
- 2.
- Mode 9: PV-powered Energy Storage (PPV ≥ 230 W)
- 3.
- Mode-11: EV to EV (V2V) Charging (PPV < PPV MIN)
- ➢
- Even though the utility grid is fully loaded due to local demand and irradiation variation on PV, EV-charging is not delayed.
- ➢
- The 11 modes based on load and source availability offer EV charging terminals an uninterrupted supply for charging.
- ➢
- The total power demand is maintained by the available vehicle and ESU.
- ➢
- A MATLAB model was developed for the charging station to analyze different types of charging stations, including multiport offerings.
- ➢
- The experimental setup analyzes the practical feasibility of charging stations.
7.2. A DC Microgrid-Based Charging Station and Its IoT-Based Monitoring System
- ➢
- The cloud delivers a swapping battery condition report to the driver’s mobile device directly after detecting unusual conditions in the battery.
- ➢
- The battery swapping parameters’ detection and storage in the cloud helps develop the business model.
7.3. Energy Management Strategy for a DC Microgrid with Maximum Penetration of RES
- PG > PL (the priority load is the lighting load that charges during the day and discharges at night)
- PG = PL (the load is raised at 9 am to 10 am to generate power, load power is 440 W, load current is 2 A, and the generated power continuously supplies the load without any interruption)
- PG < PL (from 8 pm to 12 am, the load is considered to be 900 W and available generation is 600 W)
8. Challenges and Opportunities for Charging Station Infrastructures
8.1. Challenges
- Optimal location for electric vehicle charging stations: An ideal location is critical in reducing the range of anxiety experienced by electric vehicle buyers. Several factors influence the location of charging stations, including drivers’ satisfaction with charging, operators’ economic problems, vehicle power loss, power grid safety, and transportation system and traffic congestion.
- The following problems were assumed while conducting the research:
- Charging demand (mainly by BEV)
- Charging facility features
- Charging fees and electricity cost
- Cost of station installation, operation, maintenance, and land acquisition
- Development of fast charging, ultra-fast charging, and battery swapping stations to reduce EV-charging time.
- Provision of queue management based on the strategy at the charging station.
- To maintain energy balance, a proper grid integration structure with charging stations is required.
- A communication system between the charging point to EV and grid management and the ability to quickly identify a vehicle and make the billing process as simple as possible. Charge cost optimization by selecting the most appropriate time and charging rates. Optimize grid load by adjusting charger capacity in response to grid demand. Use V2G technology to support grid operation during peak loads.
- Energy storage technologies in EV charging stations, particularly fast and ultra-fast charging stations, support stable operation, and improve customer satisfaction. In order to define their contribution level in terms of energy supply for EV-charging, ESS sizing is critical in charging station infrastructure.
- Architecture: Efficiency of the existing utility grid system is decreased due to EV charging loads.
- Adaptation of renewable sources: High cost of installation of renewable energy sources and compliance with multiple charging protocols.
- Accommodation of land space: The promotions of EV charging stations with renewable energy sources occupy large land areas that can increase the cost of installation.
- Energy management: There are many challenges in EMS, such as low efficiency at charging port, reliability and prediction of batteries from overcharging.
- DC link interfacing: Interfacing of renewables creates voltage fluctuation in DC links and requires a regulated output from the sources.
- Selection of converters: Number of switching devices and storage devices in converter topology lead to more losses in conversion. In addition, control of the converter requires a suitable control.
- Control scheme: The control methodology selection for a suitable power rating application requires detailed analysis and dedicated control.
8.2. Opportunities
- Optimal selection of charging stations based on the demand for charging (primarily from BEVs), charging facility features, fees and electricity costs, station installation, operation, and maintenance costs, as well as land acquisition costs; there is literature available on optimization.
- The optimal development of charging infrastructure necessitates careful planning in terms of charging station location and size. A large charging station can accommodate a greater number of chargers to accommodate more EVs; nevertheless, it will also require more electrical energy and construction costs.
- The charging infrastructure requirements are highly dependent on EV battery sizes and power rates, both of which are expected to rise in the future.
- Development of fast-charging, ultra-fast charging, and battery swapping stations are being developed to reduce EV-charging time.
- The rate of EV adoption has a significant impact on the development of fast- and ultra-fast charging stations, as well as the profitability of their operation.
- It is critical to regulate and schedule the available charging stations in order to charge an electric vehicle. This will aid in the strategic management of EV queues at charging stations. The management of queues will be aided by an effective communication network.
- Several communication protocols and standards are available for billing and managing the charging.
- Architecture: The charging station, by connecting renewable sources and bidirectional power converter in the charging station architecture, meets grid demand through V2G technology.
- Adaptation of renewable sources: Charging pricing decreases, emission reduces, and the utility grid does not overload.
- Accommodation of land space: The installations of more charging stations lead to an increase in the number of vehicles on the road.
- Energy management: The energy management system in charging stations with renewable sources makes full use of solar energy; thus, the operating cost is reduced, resulting in maximum benefit.
- DC link interfacing: EV-charging depends on storage devices; effectively connected DC energy storages provide better efficiency.
- Selection of converters: A suitable converter and control strategy leads to increased efficiency and reduces charging time.
- Control scheme: The conventional and intelligent control, the optimization algorithm, is used to provide better control.
9. Conclusions
- In AC microgrids, the controller can manage frequency, voltage regulation, and real and reactive power control.
- The DC microgrid-based charging station is more suitable due to conversion losses.
- The energy storage unit in the charging station provides uninterrupted EV-charging and ESU provides an option for effective usage of renewable energy sources.
- ESU integration with microgrids through dedicated converters enables fast charging and discharging.
- DC microgrid-based charging station control through DC link voltage and power prediction provides better efficiency.
- Controlling of microgrids through fuzzy logic and optimization technique-based energy management strategy provides better regulation and optimal management of fast charging.
- Charging side converters with bidirectional power flow support grid voltage regulation through constant current and voltage charging.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Charging System | Pros | Cons |
---|---|---|
Conductive charging | Suitable for slow and fast charging High-efficient charging Multiple taping possible | Need of standard connectors and cable Requires complex charging infrastructure |
Wireless charging | No problems in standardization of connectors Dynamic charging can be implemented Charging can be done in all climate conditions | Coil type needs to be standardized Cost of coil increases vehicle price Complexity increases on the location of the transmitter Losses are more in wireless charging |
Battery swapping | Battery replacement done in less than a minute With the help of swapping, distance travel is increased. | Standardization required for battery size and type Charging station should be able to manage a larger number of batteries User responsible for battery maintenance |
Charger Type | Benefits and Uses | Challenges |
---|---|---|
On-board | Charge possible at any location with an electric outlet Simple BMS can be used | Slow charging, less power transfer at a time Difficult to implement vehicle-to anything charging Weight of charger added to the EV |
Off-board | Used in higher power rating (kW) Fast charging Does not add to vehicle weight | Battery heating issue Difficult to allocate places Cost of charging is high |
Reference | Sources | Microgrid Control | Load Control |
---|---|---|---|
[61] | Solar | PI controller-based control for charging and MPPT-based control for PV to DC bus side | Proportional integral PWM generation-based first quadrant-based DC to DC converter |
[62] | PV Wind, Fuel cell | Simulation dynamic optimization SDO-based sizing for complete microgrid control | Dynamic wireless power transfer (DWPT) systems for dynamic charging |
[63] | PV, micro turbine | Rule-based algorithm with dynamic load modeling for microgrid control | Mixed integer linear programming for the energy storage unit |
[38] | PV, wind and diesel generator | The elements that make up a microgrid can be optimally dimensioned and managed | Lead-acid battery-aging models and average ambient temperature and control |
[64] | PV, wind, biomass, and diesel generator | Invasive weed optimization algorithm | Backtracking search algorithm control |
Reference | Renewables | Microgrid Control | ESU Capacity | EV Type | EV Charging and Load Control |
---|---|---|---|---|---|
[71] | PV | Droop control | - | PEV | Load regulation through over-voltage and over-current regulation control |
[50] | PV | Dynamic optimal power flow control | 1000 kWh | PEV | Smart load management control strategy based on cost estimation from generating energy and losses |
[72] | PV | Rule-based control of DC LINK voltage | 130 Ah | PHEV | PI-PWM control of charging |
[18] | PV | Power management control | (SMES) 6 H/300 A | EV | PI controller-based charging of EV and superconducting magnetic energy Storage (SMES) |
[73] | PV | Circulating currents elimination | - | EV | Accumulated total neutral-point current control used to reduce voltage ripple in charging output. |
[74] | PV, Wind | Model predictive controller (MPC) | 24 kWh | EV | Constant current and voltage loop control |
Reference | Renewables | Microgrid Control | EV Type/Motor | EV Charging and Load Control |
---|---|---|---|---|
[82] | PV | DC link voltage-based control | PHEV | Control of load depends on the SOC available at the vehicle battery, based on the reference level operated in CV or CC mode |
[83] | PV | Rule-based control | PHEV | Load current requirement is measured by power conditioner monitors |
[84] | PV | Fuzzy logic power-flow controller | PHEV | Based on the real-time estimation of the load availability with total generating cost-based prediction control |
[85] | PV and wind | Supervisor control | Different AC and DC loads | Custom-made supervisor control capable to efficiently administrate diverse energy |
[66] | Wind | LabView control algorithm | Brushed PM DC motor | Relationship between frequency and DC voltage-based control |
Reference | Renewables | Microgrid Control | Load | ESU Capacity | Load Control |
---|---|---|---|---|---|
[92] | PV | Two types of algorithm are used—stochastic dynamic programming (SDP) algorithm and greedy algorithm (benchmark algorithm) | EV | - | A linear regression model is used for load prediction and control |
[93] | - | The smart metering-based microgrid control is used with Modbus on an TCP/IP connection using the internal LAN | EV | 30 kVA | An SOC prediction-based load control is followed. |
[94] | PV | EMS is used to optimize power generation and use of different sources and loads to minimize the total cost, while satisfying the load and device constraints. | EV | Optimization | Keeping in mind the high loading impacts of the EV, typical EV-charging methods were incorporated. |
[64] | PV and Wind | Frequency-based control | Balanced load | 7.3 MWh | The frequency and SOC-based control are used to provide high-quality power to the connected loads |
[17] | PV&Wind | Supervisor control | Different AC & DC Load | Custom-made supervisor control capable to efficiently administrate the diverse energy forms |
Reference | Renewables | Microgrid Control | ESU Capacity | Load Control |
---|---|---|---|---|
[75] | PV, wind | Power-based, rule-based control | Battery | Electromagnetic transient program |
[106] | PV | Coordinated rule-based control with P&O MPPT | 250 kW | The direct torque (DTC) and direct power control (DPC) |
[107] | PV, wind | Wavelet Transform and Fuzzy Control-based microgrid control. | - | The fuzzy control is adopted to optimize the energy management control of EVs |
[108] | PV, wind, supercapacitor, and fuel cell | Pulse width modulation (PWM)-based power factor correction (PFC) control | - | Constant voltage and constant current control method |
[109] | PV | Hybridization algorithm of Particle Swarm Optimization (PSO) and Applied Artificial Physics (APO) | - | Voltage control loop (VCL) and current control loop (CCL) |
Ref. | Renewables | Microgrid Control | Type of EV Connected | ESU Capacity | Load Control |
---|---|---|---|---|---|
[114] | PV | Power balance control using the state diagram method | EV | - | This involves DC-based charging with Chademo and the Combined Charging Standard (CCS). |
[115] | PV | DC link voltage-based converter control | EV | 2 kW | PI control of charging point |
[29] | - | PWM-based bidirectional converter control | Battery storage | 2.16 kWh | Inductively coupled power transfer (ICPT)-based pulse charging |
[116] | PV | MPPT controller | Battery storage | - | Different operating modes manage the charging |
[117] | PV | PWM control | Battery Bank | - | Conventional current hysteresis control method |
Reference | Renewables | Microgrid Control | Type of EV Connected | ESU Capacity | Load Control |
---|---|---|---|---|---|
[91] | PV | Rule-based control with PSO-based microgrid control | EV1 | 150 kW | SOC-based charging control |
[121] | - | The power flow to all the port is connected through the high frequency link transformer | EV1 | 5 kW | PWM-based control strategy used for EV charging by controlling gate pulse. |
[122] | PV | MPPT control | - | 10 kW | PWM-based control strategy |
[123] | PV | MPPT control | - | 3.3 kW | Current sharing algorithm. |
[124] | PV | Power flow | - | - | Rule-based control |
Microgrid Architecture | Isolated DC Microgrid | Grid Connected RES Powered DC Microgrid | DC Microgrid with Direct Connections of ESU | AC Bus Charging Station Architecture | Hybrid AC-DC Microgrid | Multiport Converter with DC Grid Interconnection | Multiport Converter with AC Grid Interconnection Grid |
---|---|---|---|---|---|---|---|
Direct DC charging (with no AC conversion) | Yes | Yes | Yes | No | Yes | Yes | Yes |
Direct AC usage for local load | No | Yes | Yes | Yes | Yes | Yes | Yes |
Feasible low amount of conversion losses during V2Any (Vehicle and Grid) | Yes | Yes | Yes | No | No | Yes | Yes |
Fast charging and discharging of ESU | Yes | Yes | No | No | Yes | Yes | Yes |
Used for high power rating | Yes | Yes | Yes | Yes | Yes | No | No |
Reliability | Medium | High | High | Low | Low | Medium | Medium |
Scalability | Medium | High | Medium | High | Low | Medium | Medium |
Stability | Stable | Stable | Stable | Stable | Unstable | Stable | Stable |
Standard | Scope | Type | Year |
---|---|---|---|
SAE J1772 | Define connectors for AC charging | Conductive | 2010 |
SAE J2293-2 | Communication network between electric vehicle supply equipment (EVSE) and EV; this communication follows an Enhanced Transmission Selection (ETS) network. | Conductive | 2014 |
SAE J2847-1 | Provides standard communication between the utility grid and plug-in electric vehicles. | Conductive | 2010 |
SAE J2847-2 | This standard defines an off-board conductive DC charger and its communication with plug-in electric vehicles. | Conductive and Inductive | 2015 |
SAE J2954 | This defines a wireless power transfer of all types of plug-in electric vehicles and its coil alignment methodology | Inductive | 2020 |
IEC 61980-3 | Defines the magnetic field-based wireless power system and its specific requirements. | Inductive | 2019 |
IEC TS 62840-1 | Gives a general overview for battery swap systems | Battery swapping | 2016 |
IEC 61851-1 | Defines EVSE when it is charging from the voltage range of 1000V to 1500V AC or DC, including on-board rechargeable energy storage systems (RESS) | Conductive | 2017 |
IEC 61851-21-1 | Defines requirements for conductive connection of an electric vehicle (EV) to an AC or DC supply | Conductive | 2017 |
IEC 61851-24 | Defines a digital communication between a DC charging station and an EV | Conductive | 2014 |
IEC 60364 | Describes power generation and distribution of electrical charging station installations in buildings | Conductive &Inductive | 2017 |
IEE2030.1.1-2015 | DC quick charger for use with electric vehicles | Fast charging | 2016 |
GB/T 29317 | The terminology of electric vehicle charging/battery swap infrastructure | Battery swapping | 2012 |
Levels | Supply Type | Voltage Range | Current Range | Power Output | PEV Charging Time | Types of Chargers | EV Connector |
---|---|---|---|---|---|---|---|
AC Level 1 | Single phase AC | 120 V 240 V | 16 A 13–16 A | 1.9 kW 3 kW | 7 h | On-board | J1772™/AC |
AC Level 2 | Single/three phase AC | 208–240 V | 80 A | 20 kW | 3 h | On-board | J1772™/AC |
AC Level 3 | three phase AC/Como charging | 300–600 V | 400 A max | 120–240 kW | 30 min | On-board | CHAdeMO |
DC Level 1 | DC | 200–500 V | <80 A | 40 kW | 22 min | Off-board | J1772™/AC |
DC Level 2 | DC | 200–500 V | <200 A | 100 kW | 10 min | Off-board | CHAdeMO/DC SAE/DC |
DC Level 3 | DC | 200–600 V | <400 A | 240 kW | 30 min | Off-board | CHAdeMO/DC SAE/DC |
Reference | Converter | Control | Feature |
---|---|---|---|
[135,141,142] | Three-Level Three-Phase NPC Converter | Voltage Oriented Control |
|
[137,143] | Three-phase bridgeless boost converter | Sliding mode control |
|
[144] | Unidirectional multilevel converter. | PWM based control |
|
[145] | Symmetrical two-device unidirectional boost converter | PWM based control |
|
Ref. | Converter | Control | Feature |
---|---|---|---|
[146] | Bidirectional PV-Cuk converter | Maximum power point tracking (MPPT) |
|
[147] | Interleaved high gain DC-DC converter | Voltage lift technique |
|
[113] | Transformer less high gain boost and buck-boost DC-DC converters | Voltage control |
|
[148] | Single-Ended Primary Inductance Converter (SEPIC) | MPPT and Fuzzy |
|
Charging Side DC-DC Converters | |||
---|---|---|---|
Ref | Converter | Control | Feature |
[149,150] | Multiple Interleaved Buck Converters | Discrete-Time Model and Direct Control |
|
[151] | Full-Bridge LLC Resonant Converter | PFM (Pulse Frequency Modulation) and PI control. |
|
[152] | Dual Active Bridge | Current sharing control |
|
[153] | DC/AC/DC Converter | e PWM modulation factor value and thereby controls |
|
[154] | Two-Phase Series-Capacitor DC-DC Buck Converter | EnhancedI2 control |
|
Ref. | System Architecture | Charging Station Control Strategy | Power Converter Topologies Used and Control Methodology |
---|---|---|---|
[159,160] | Isolated DC microgrid for EV-charging | Rule-based control using power balancing control, optimal power self-scheduling of power balancing control | A dedicated DC-DC converter is used. Differential evaluation based on SOC predicted that charging minimizes total energy cost |
[86,161,162] | Grid-connected RES powered DC microgrid for EV-charging | PV-based battery charging stations considering service availability, DC link power predictive model (PPM) for charging station control | Dual stage-controlled DC-DC converter along with the optimization algorithm for charging |
[163] | RES-powered DC microgrid with ESU | DC link voltage-based control | Dedicated DC-DC converter for PHEVs charging; it uses minimum energy from the utility grid |
[164,165] | AC bus-coupled charging station architecture | Control area network (CAN) -based charging station control | Charging of EV with AC-DC bidirectional converters; it works in both inverter and rectifying mode |
[166,167] | Hybrid AC-DC Microgrid | Power oscillation damping control implemented for both ESU and other devices connected to the microgrid | SOC-based charging of EV is done based on DC link voltage and is controlled through a DC-DC converter. Charging and discharging of ESU operates inner current loop control outer voltage/frequency control |
[168,169,170] | Multiport converter-based DC micro grid | DC bus voltage is maintained through the PI and fuzzy controller. | Two loop control of battery charging is followed as constant current and constant voltage control |
[171] | Multiport converter-based AC micro grid | Dual active bridge-based, control-based current sharing error compensation | Dual output port controlled for charging based on the realized DC voltage |
Parameters | DC Bus Voltage | Capacity of Wind Generator | Capacity of PV Panel | Capacity of Fuel Cell Power | Battery Type | Battery Capacity | DC-DC Converter | Lamp Loads | Load Bus | Diesel Generator | Maximum Current |
---|---|---|---|---|---|---|---|---|---|---|---|
Specification | 24 V | 200 W | 200 W | 100 W | Tall tubular C10 | 14 Ah/12 V | 24 V/220 V | 500 W | 220 V | 500 W | 3 A |
Time | PV Power (W) | Wind Power (W) | Fuel Cell Power (W) | Loads (W) | Batteries | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Generated Power (W) | Priority Load | Commercial Load | Net Lads | Priority Load | Commercial Load | ||||||||||
P (W) | I (A) | P (W) | I (A) | P (W) | I (A) | P (W) | I (A) | P (W) | I (A) | P (W) | I (A) | ||||
8 p.m.–12 a.m. | 0 | 150 | 100 | 250 | 1.13 | 100 | 0.5 | 250 | 1.1 | 350 | 1.6 | 100 | 0.5 | 100 | 0.45 |
9 a.m.–10 a.m. | 200 | 140 | 100 | 440 | 2 | 100 | 0.5 | 340 | 1.5 | 440 | 2 | −100 | −0.5 | 0 | 0 |
7 a.m.–8 a.m. | 100 | 170 | 100 | 370 | 1.68 | 100 | 0.5 | 150 | 0.7 | 250 | 1.2 | −100 | −0.5 | −120 | −0.7 |
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Savio Abraham, D.; Verma, R.; Kanagaraj, L.; Giri Thulasi Raman, S.R.; Rajamanickam, N.; Chokkalingam, B.; Marimuthu Sekar, K.; Mihet-Popa, L. Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids. Electronics 2021, 10, 1895. https://doi.org/10.3390/electronics10161895
Savio Abraham D, Verma R, Kanagaraj L, Giri Thulasi Raman SR, Rajamanickam N, Chokkalingam B, Marimuthu Sekar K, Mihet-Popa L. Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids. Electronics. 2021; 10(16):1895. https://doi.org/10.3390/electronics10161895
Chicago/Turabian StyleSavio Abraham, Dominic, Rajesh Verma, Lakshmikhandan Kanagaraj, Sundar Rajan Giri Thulasi Raman, Narayanamoorthi Rajamanickam, Bharatiraja Chokkalingam, Kamalesh Marimuthu Sekar, and Lucian Mihet-Popa. 2021. "Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids" Electronics 10, no. 16: 1895. https://doi.org/10.3390/electronics10161895
APA StyleSavio Abraham, D., Verma, R., Kanagaraj, L., Giri Thulasi Raman, S. R., Rajamanickam, N., Chokkalingam, B., Marimuthu Sekar, K., & Mihet-Popa, L. (2021). Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids. Electronics, 10(16), 1895. https://doi.org/10.3390/electronics10161895