Description:TITLE OF THE INVENTION: SYSTEM AND METHOD TO ENHANCE THE CHARGING EFFICIENCY OF AN ENERGY STORAGE SYSTEM WITH REDUCED THERMAL MANAGEMENT SYSTEM USAGE AND REDUCED CHARGING TIME
FIELD OF THE INVENTION
The present disclosure is generally related to charging systems of electric vehicles. Particularly, the present disclosure is related a system and method, to enhance the charging of an energy storage system of an electric vehicle, at a charging station. More particularly, the present disclosure is related to a system and method, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time.
BACKGROUND OF THE INVENTION
In electric/electronics system, derating is defined as the phenomenon to run the system at its lower power (or current, or energy) limit than maximum capability to keep the system safe from any malfunctioning. Said derating technique can also be utilized with an energy storage system as well. The derating technique can be classified based on the direction of current (e.g., charging and discharging) and stress factor, such as voltage, current, state of charge (SOC), temperature, internal resistance and critical errors.
In electric vehicles, the derating technique based on voltage, state of current (SOC), and temperature are widely used during the charging of the energy storage system, for protecting the energy storage system from permanent fault and fire. However, utilizing of the derating technique during the charging of the energy storage system slows down the charging speed.
In case of temperature-based derating, a thermal management system (for example, a chiller) is utilized to control the temperature of the energy storage system, during charging. However, the usage of the thermal management system increases the energy demand from the energy storage system during high temperature.
In case of SOC-based derating, the maximum capacity of the energy storage system is not used. To outperform this shortcoming, an enhanced derating technique is required to charge the energy storage system at its maximum capacity with safety margin. For example, to maximize the usage of the electric vehicle, charging of the energy storage system at a faster charging rate is required.
Most of the conventional derating technique are simple look-up techniques that can be implemented easily. However, there is no close loop technique that can evaluate the derating factor based on the health, environmental temperature and future trip information of the electric vehicle’s energy storage system.
Further, with the existing derating technique, the charging time of electric vehicles increases significantly due to derated charging current. Other side, the usage of thermal management system is increased to maintain the temperature of the electric vehicle’s energy storage system.
There is, therefore, a need in the art, for: a system and method, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, which overcomes the aforementioned drawbacks and shortcomings.
OBJECTIVES OF THE INVENTION
A primary objective of the disclosure is to provide a system and method to enhance the charging efficiency with reduce thermal management system usage, while charging of an energy storage system of an electric vehicle, at a charging station.
Another objective of the disclosure is to provide a system and method to enhance the charging efficiency with reduce charging time, while charging of an energy storage system of an electric vehicle, at a charging station.
Yet another objective of the disclosure is to provide a system and method that envisages the trip and other parameters, such as environmental temperature based on the past drive pattern and environmental condition.
Yet another objective of the disclosure is to provide a system and method that evaluates the energy demand to drive the electric vehicle for charging at the charging station from its current location based on the envisaged trip and other parameters of the energy storage system of the electric vehicle.
Yet another objective of the disclosure is to provide a system and method that evaluates a derating factor based on the envisaged trip and other parameters, and the evaluated energy demand to drive the electric vehicle to the charging station from its current location.
Yet another objective of the disclosure is incorporating the state of health of the energy storage system in terms of ohmic resistance increment with aging while evaluating the derating factor.
Yet another objective of the disclosure is to modify the speed of the electric vehicle based of the evaluated derating factor to reduce the thermal management system usage during charging
SUMMARY OF THE INVENTION
A system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, is disclosed. Said system broadly comprises: a charging station; a centralized data collection member; an envisaging member; a derating member; an energy module; and a vehicle control unit.
The charging station broadly comprises: a plurality of charging modules; and a surveilling and communication module. Each charging module among the plurality of charging modules comprises a charger and a charger communication interface. Each charging module among the plurality of charging modules facilitates charging of an electric vehicle independently.
Said surveilling unit facilitates surveilling of an at least an environmental parameter of the energy storage system and the charging station, in real-time, with the surveilled data being transmitted to the centralized data collection member, with the help of the communication interface.
The energy module is disposed on the electric vehicle. Said energy module comprises: an energy storage system, and a thermal management system. Said thermal management system facilitates to maintain the energy storage system in optimum temperature, and said energy storage system delivers power to the electric vehicle.
The vehicle control unit is disposed on the electric vehicle. Said vehicle control unit facilitates collecting and transmitting a historical trip data of the electric vehicle, and a plurality of vehicle data, in real-time, to the centralized data collection member.
The centralized data collection member broadly comprises: an at least one gateway member; an internet cloud; and a distributed data collection center.
The real-time data collected from the plurality of charging modules in the charging station are transmitted first to an internet cloud with the help of the at least one gateway member, and finally to a distributed data collection center. Similarly, the data from the distributed data collection center is transmitted to the plurality of charging modules with the help of the internet cloud and the at least one gateway member.
The envisaging member broadly comprises: an envisaging module, and an EV simulating module.
The envisaging module collects: the data shared by the vehicle control unit about the electric vehicle, and the data shared by the charging station, from the centralized data collection member.
Said data collected from the centralized data collection member are first pre-processed to remove the outliers. Said pre-processed data being transmitted to the envisaging module.
The envisaging module is configured to facilitate the envisaging of next trip driving pattern of the electric vehicle, and the EV simulating module envisages the required current and voltage, for charging the electric vehicle, to enhance the charging efficiency of the energy storage system of an electric vehicle, at the charging station.
In an embodiment, said envisaging module is configured based on a machine learning technique, such as support vector regression, support vector machine, or the like.
The derating member is disposed on the electric vehicle, and is associated with the energy module and the vehicle control unit to evaluate a derating factor to control the speed of the electric vehicle, while said electric vehicle being coming towards the charging station.
Said derating member broadly comprises an ESS surveilling unit, an estimation module, a derating controller, and a derating communication interface.
The ESS surveilling unit is configured to surveil an at least a parameter of the energy storage system, in real-time, with: the surveilled at least one parameter being transmitted to an estimation module.
The estimation module estimates the state of charge (SOC) and ohmic resistance of the energy storage system.
The derating controller collects data from the vehicle control unit and from the centralized data collection member with the help of the derating communication interface and evaluates the derating factor to control the speed of the electric vehicle.
Said ESS surveilling unit, and said estimation module are communicatively associated with each other, and are embedded on the derating controller. In an embodiment, the derating controller is a microcontroller.
The method of working of said system is also disclosed.
The disclosed system (and/or method) offers at least the following advantages: helps to avoid slow charging due to temperature based derated conditions; helps to reduce the cooling time of the energy storage system during charging; helps to operate the energy storage system within safe operating temperature limits; optimizes the energy requirement for charging during the charging of the electric vehicle at the charging station; optimizes the charging time of the electric vehicle at the charging station; helps to charge the energy storage system with maximum allowable current with minimal derating; utilizes the effect of ageing with estimated ohmic resistance for derating factor evaluation of the energy storage system; and supports to improve the performance of the energy storage system in terms of cycle counts.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 illustrates a system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, in accordance with an embodiment of the present disclosure;
Figure 2 illustrates a charging station of a system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, in accordance with another embodiment of the present disclosure;
Figure 3 illustrates a process flow of transmitting data collected from an electric vehicle and data from a charging station to a centralized data collection member, in real-time, in accordance with an embodiment of the present disclosure;
Figure 4 illustrates a process of envisaging the current and voltage based on an envisaged the trip and other parameters of an electric vehicle, in accordance with an embodiment of the present disclosure;
Figure 5 illustrates a derating member of a system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, in accordance with another embodiment of the present disclosure;
Figure 6 illustrates a first-order electrical equivalent circuit model of an energy storage system, in accordance with another embodiment of the present disclosure; and
Figure 7 illustrates a method of evaluating derating factor in a system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, in accordance with another embodiment of the present disclosure.
DETAILED DESCRIPTION OF THE INVENTION
Throughout this specification, the use of the words “comprise” and “include”, and variations, such as “comprises”, “comprising”, “includes”, and “including”, may imply the inclusion of an element (or elements) not specifically recited. Further, the disclosed embodiments may be embodied, in various other forms, as well.
Throughout this specification, the use of the word “system” is to be construed as: “a set of technical components (also referred to as “members”) that are communicatively and/or operably associated with each other, and function together, as part of a mechanism, to achieve a desired technical result”.
Throughout this specification, the use of the words “communication”, “couple”, and their variations (such as communicatively), is to be construed as being inclusive of: one-way communication (or coupling); and two-way communication (or coupling), as the case may be, irrespective of the directions of arrows, in the drawings.
Throughout this specification, where applicable, the use of the phrase “at least” is to be construed in association with the suffix “one” i.e. it is to be read along with the suffix “one”, as “at least one”, which is used in the meaning of “one or more”. A person skilled in the art will appreciate the fact that the phrase “at least one” is a standard term that is used, in Patent Specifications, to denote any component of a disclosure, which may be present (or disposed) in a single quantity, or more than a single quantity.
Throughout this specification, where applicable, the use of the phrase “at least one” is to be construed in association with a succeeding component name.
Throughout this specification, the use of the word “plurality” is to be construed as being inclusive of: “at least one”.
Throughout this specification, the use of the word “vehicle”, and its variations, is to be construed as being inclusive of: “commercial electrical vehicles (CEV)”.
Throughout this specification, the use of the phrase “electric vehicle”, and its variations, is to be construed as being inclusive of: “a vehicle that can only be powered, by an electric motor, and (or which) draws electricity, from an energy storage system (all-electric vehicle); and a vehicle that can be powered, by: an electric motor, which draws electricity, from an energy storage system; and an internal combustion engine (plug-in hybrid electric vehicle)”.
Throughout this specification, the use of the phrase “energy storage system”, the acronym “ESS”, and variations, is to be construed as being inclusive of: “battery modules; battery packs; battery systems; and/or the like”.
Throughout this specification, the use of the word “battery”, and its variations, is to be construed as being inclusive of: “lithium-ion batteries”.
Throughout this specification, the phrases “charging station” and “charging depot” are used interchangeably.
Throughout this specification, the words “the” and “said” are used interchangeably.
Throughout this specification, the phrases “at least a”, “at least an”, and “at least one” are used interchangeably.
Throughout this specification, where applicable, the phrase “energy storage system” and the word “battery” are used interchangeably.
Throughout this specification, the use of the word “surveilling”, and its variations, is to be construed as being inclusive of: “tracking; monitoring; recording; sensing; measuring; and/or the like”.
Throughout this specification, the disclosure of a range is to be construed as being inclusive of: the lower limit of the range; and the upper limit of the range.
Also, it is to be noted that embodiments may be described as a method. Although the operations, in a method, are described as a sequential process, many of the operations may be performed in parallel, concurrently, or simultaneously. In addition, the order of the operations may be re-arranged. A method may be terminated, when its operations are completed, but may also have additional steps.
A system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station (also referred to as “system”), with reduced thermal management system usage and reduced charging time, is disclosed. In an embodiment, as illustrated in Figure 1, said system broadly comprises: a charging station (1000); a centralized data collection member (2000); an envisaging member (3000); a derating member (5000); an energy module (6000); and a vehicle control unit (4000).
In another embodiment of the present disclosure, said energy module (6000) broadly comprises: an energy storage system (6200), and a thermal management system (6100; for example, a chiller).
Said thermal management system (6100) facilitates to maintain the energy storage system (6200) in optimum temperature, and said energy storage system (6200) delivers power to the electric vehicle.
In yet another embodiment of the present disclosure, the derating member (5000) is disposed on the electric vehicle. Said derating member (5000) is associated with the energy module (6000) and the vehicle control unit (4000) to evaluate a derating factor to control the speed of the electric vehicle, while said electric vehicle is coming towards the charging station.
Said vehicle control unit (4000), and said energy module (6000) are disposed on the electric vehicle.
Said charging station (1000), said vehicle control unit (4000), said envisaging member (3000), and said derating member (5000) are communicatively associated with said centralized data collection member (2000).
Similarly, said energy module (6000), and said vehicle control unit (4000) are communicatively associated with said derating member (5000).
A historical trip data of the electric vehicle maintained (or stored) in the vehicle control unit (4000) is transmitted to the centralized data collection member (2000). Similarly, a plurality of vehicle data, such as current location, speed, acceleration, available charge level of the energy storage system, etc., in real-time, are also transmitted, by the vehicle control unit (4000), to the centralized data collection member (2000).
In yet another embodiment of the present disclosure, as illustrated in Figure 2, said charging station broadly comprises: a plurality of charging modules (1100; for example, “n” number of charging modules); and a surveilling and communication module (1200). Each charging module among the plurality of charging modules (1100) comprises: a charger and a charger communication interface.
Each charging module among the plurality of charging modules (1100) facilitates charging of an electric vehicle independently.
Data collected from the electric vehicle coming for charging, and at the charging station, in real-time, are transmitted to the centralized data collection member (2000) with the help of the vehicle control unit (4000) and respective charger communication interface, respectively.
Real-time data from the electric vehicle such as energy storage system parameters (e.g., current, voltage, surface temperature), speed, acceleration, etc. are transmitted, by the vehicle control unit (4000), to the centralized data collection member (2000).
The surveilling and communication module (1200) comprises: a surveilling unit, and a communication interface. Said surveilling unit facilitates surveilling of an at least an environmental parameter (for example, temperature) of the energy storage system (6200) and the charging station (1000), in real-time.
The at least one environmental parameter surveilled by the surveilling unit, in real-time, is transmitted to the centralized data collection member (2000), with the help of the communication interface.
In yet another embodiment of the present disclosure, as illustrated in Figure 3, the centralized data collection member (2000) broadly comprises: an at least one gateway member (2001; for example, a touter); an internet cloud (2002); and a distributed data collection center (2003).
The real-time data collected from the plurality of charging modules (1100) in the charging station (1000) are transmitted first to an internet cloud (2002) with the help of the at least one gateway member (2001), and finally to a distributed data collection center (2003). Similarly, the data from the distributed data collection center (2003) is transmitted to the plurality of charging modules (1100) with the help of the internet cloud (2002) and the at least one gateway member (2001).
The envisaging member (3000) is configured to envisage the current and voltage required for charging the electric vehicle, to enhance the charging efficiency of the energy storage system (6200) of an electric vehicle, at the charging station (1000), with reduced thermal management system usage and reduced charging time.
The process of envisaging the current and voltage by the envisaging member (3000) is illustrated in Figure 4. Said envisaging member (3000) broadly comprises: an envisaging module (3200); and an EV simulating module (3400).
The envisaging module (3200) collects: the data shared by the vehicle control unit (4000) about the electric vehicle, and the data shared by the charging station (1000), from the centralized data collection member (2000).
Said data collected from the centralized data collection member (2000) are first pre-processed (3100) to remove the outliers. Said pre-processed data being transmitted to the envisaging module (3200).
In yet another embodiment of the present disclosure, said envisaging module (3200) is configured based on a machine learning technique, such as support vector regression, support vector machine, or the like.
Said envisaging module (3200) is configured to facilitate the envisaging of next trip driving pattern of the electric vehicle (3300), including speed, acceleration, and the environmental parameters of the energy storage system (6200). Said envisaged data are shared with the centralized data collection member (2000) as well.
Then, the envisaged data (3300) from the envisaging module (3200) is transmitted to the EV simulating module (3400) to envisage the required current and voltage, for charging the electric vehicle, to enhance the charging efficiency of the energy storage system (6200) of an electric vehicle, at the charging station (1000).
The derating member (5000) of the system is illustrated in Figure 5. In yet another embodiment of the present disclosure, said derating member (5000) broadly comprises: an ESS surveilling unit (5100); an estimation module (5200); a derating controller (5300); and a derating communication interface (5400).
Said ESS surveilling unit (5100), and said estimation module (5200) are communicatively associated with each other, and are embedded on the derating controller (5300).
In yet another embodiment of the present disclosure, the derating controller (5300) is a microcontroller.
The ESS surveilling unit (5100) is configured to surveil an at least a parameter of the energy storage system (6200), in real-time, with: the surveilled at least one parameter being transmitted to the estimation module (5200).
In yet another embodiment of the present disclosure, the at least one parameter includes, but is not limited to: voltage; current; temperature; and/or the like.
Based on the data received from the ESS surveilling unit (5100), the estimation module (5200) estimates the state of charge (SOC) and ohmic resistance of the energy storage system (6200). The output from the estimation module (5200) is forwarded to the derating controller (5300).
Further, to evaluate the derating factor to control the speed of the electric vehicle, the derating controller (5300) collects data from the vehicle control unit (4000) and from the centralized data collection member (2000) with the help of the derating communication interface (5400).
The data collected from the vehicle control unit (4000) and from the centralized data collection member (2000) includes, but is not limited to, energy storage system parameters (e.g., current, voltage, temperature), vehicle speed, vehicle acceleration, and environmental parameter (for example, temperature) of the charging station (1000).
The load current is directly related with the change in temperature of the energy storage system. If the speed of the electric vehicle changes, the demand in load current will also change, thereby causes the energy storage system temperature to change. Hence, to perform the charging at the maximum allowed rate, the energy storage system should be kept at an optimum temperature at the beginning of charging.
For SOC estimation, model-based estimation technique based on non-linear filter can be used. In this model Kalman filter is used. Though, the accuracy of battery model parameters is important to achieve high SOC estimation. To achieve high estimation accuracy at low computational cost, electrical equivalent circuit model is used.
A first order electrical equivalent circuit model (5210; 1-RC), as illustrated in Figure 6, is used to simulate the ESS in use. Said 1-RC consists of internal ohmic resistance (R0), electrochemical polarization/diffusion resistance (R1), and polarization/diffusion capacitance (C1), connected in parallel to form a resistance-capacitor branch, and a controller voltage source equivalent to open circuit voltage (OCV), function of SOC, and temperature.
In yet another embodiment of the present disclosure, for the model parameters identification, the forgetting factor recursive least square technique is used.
By using Kirchhoff’s voltage law and applying the Laplace transformation on the first order battery model (5210), the continuous-time voltage equations can be written as:
V_OCV (t)=(R_1/(?C_1 R?_1 s+1)+R_0 )I(t)+V_t (t)
Further, the above equation can be written in the discrete form as:
V_(t,k)=(1-a_1 ) V_(OCV,k)+?a_1 V?_(t,k-1)+?a_2 I?_k+?a_3 I?_(k-1)
Where a_1, a_2, and a_3 are the coefficients. k is the discrete-time instant.
For the real-time parameter identification of first-order electrical equivalent circuit battery model (5210), parameters such as (R0,k-1), (R1,k-1), (C1,k-1), and (Vocv,k-1), the recursive least square (RLS) technique can be used. Under which the last recorded value of the measured battery parameters such as current (Ik) and voltage (Vt,k) are utilized.
Recursive Least Square can be described by the equation as
{¦((?_r ) ^(k)=(?_r ) ^(k-1)+?(k)[y(k)-? ^^T (k) (?_r ) ^(k-1)]@?(k)=((P(k-1) ?_r (k)))/((?+?^T (k)) P(k-1)?(k))@P(k)=([(I-?(k) ?^T (k))P(k-1)])/?)¦
Where, measurement vector ?(k)=[¦(1&¦(-I_k&-V_(t,k)&-V_(t.k-1) ))]^T,K(k) refers to the gain matrix and model parameter vector ?(k)=[¦((1-a_1 ) V_(OCV,k)&¦(a_1&a_2&a_3 ))]^T.P(k) is the noise covariance matrix. y(k) is the battery model terminal voltage output. The forgetting factor (?)is set to 0.99. k is the sample time.
Based on the evaluated ?(k) using RLS, the battery model parameters can be identified by using the expression given below:
[¦(V_(OCV,k)@R_(0,k)@¦(R_(1,k)@C_(1,k) ))]=[¦(a_1/((1-a_1))@(-(a_2-a_3))/((1+a_1))@¦((2(a_1 a_2+a_3))/((1+a_1^2))@?(1+a_1)?^2/(4((a_1 a_2+a_3))))]
A method of evaluating derating factor in the system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, is illustrated in Figure 7.
Based on the driving pattern between current location and charging depot, in step S101, and the estimated SOC(t), and OCV(t) in step S102, the total envisaged energy demand (E_D) for the electric vehicle to reach the charging depot (1000) is evaluated by the expression given below:
E_D (t+D)=?_t^(t+D)¦?I(t).Vt(t) ?
Where, 't' is the start time of forecasted the next trip, and D is the total time reach the electric vehicle to the charging depot (1000). I(t) and Vt(t) is the envisaged current and voltage of the energy storage system (6200).
In step S103, with the use of evaluated E_D to drive the electric vehicle to the charging depot (1000), the value of the SOC at time ‘t+D’ is determined by using the expression given below:
SOC(t+D)=(E_D (t+D))/(Q×SOH(t)×(Uocv(t+D)-Uocv(t)))+SOC(t)
Where, Q is the actual capacity of the energy storage system (6200), Uocv(t+D) is the identified open circuit voltage from RLS technique using the envisaged current and voltage data at time ‘(t+D)’.
In step S104, SOH(t) is the state of health of the battery determined by using the expression as given below:
SOH(t)=(1-(R0(t)-R0(new))/R0(new) )
Where, R0(new) is the ohmic resistance of the new energy storage system of the electric vehicle.
In Step S106, based on the envisaged driving pattern between the current location and charging depot (1000), the total temperature rise of the electric vehicle energy storage system (T_D) for the electric vehicle to reach the charging depot (1000) is proportional to the total heat generation (H_D), it can be expressed by the expression given below:
H_D (t+D)=?_t^(t+D)¦??I(t)?^2.R0(t) ?.t
Where H_D is the sum of the irreversible heat generation due to loss of active material and current collector and reversible heat generation due to change in entropy from intercalation and deintercalation lithium-ions.
In Step S107, based on the evaluated total heat generation at time ‘t+D’, the value of the envisaged temperature (T_D) at time ‘t+D’ can be determined by using the developed relationship between heat generation and temperature rise from the past data of the electric vehicle’s energy storage system (6200) as temperature rise is a function of heat generation.
In step S108, the envisaged T_D is compared with the T_Limit, and the derating factor (D.F) is determined, to control the speed of the electric vehicle coming for charging at the charging station (1000), to reduce the usage of the thermal management system (6100) and to reduce the charging time. The value of D.F can be evaluated using the expression given below:
D.F(t)={¦(1 ; S(t)=S_min@S.F×((T_D-T_Limit) )/T_Limit ; S(t)>S_min )¦
Where, S(t) refers to the speed of the electric vehicle at time ‘t’ and S_min is the minimum speed set by a user. S.F is the safety factor that vary in the range of 0 to 1.
In Step S109, based on the evaluated D.F(t), the speed of electric vehicle at time step ‘t+1’ is evaluated by using the expression given below:
S(t+1)=D.F(t)×S(t)
The Speed of the commercial electric vehicle will be derated based on the D.F until it reaches the charging station (1000) so that the energy storage system (6200) can be charged at its maximum charging current limit.
The disclosed system (and/or method) offers at least the following advantages: helps to avoid slow charging due to temperature based derated conditions; helps to reduce the cooling time of the energy storage system during charging; helps to operate the energy storage system within safe operating temperature limits; optimizes the energy requirement for charging during the charging of the electric vehicle at the charging station; optimizes the charging time of the electric vehicle at the charging station; helps to charge the energy storage system with maximum allowable current with minimal derating; utilizes the effect of ageing with estimated ohmic resistance for derating factor evaluation of the energy storage system; and supports to improve the performance of the energy storage system in terms of cycle counts.
Implementation of the disclosure can involve performing or completing selected tasks manually, automatically, or a combination thereof. Further, according to actual instrumentation of the disclosure, several selected tasks could be implemented, by hardware, by software, by firmware, or by a combination thereof, using an operating system.
For example, as software, selected tasks according to the disclosure could be implemented, as a plurality of software instructions being executed, by a computing device, using any suitable operating system.
In yet another embodiment of the disclosure, one or more tasks, according to embodiments of the disclosure, is (or are) performed, by a data processor, such as a computing platform, for executing a plurality of instructions. Further, the data processor includes a processor, and/or non-transitory computer-readable medium, for storing instructions and/or data, and/or a non-volatile storage, for storing instructions and/or data. A network connection, a display, and/or a user input device, such as a keyboard (or mouse), are also provided.
It will be apparent to a person skilled in the art that the above description is for illustrative purposes only and should not be considered as limiting. Various modifications, additions, alterations, and improvements, without deviating from the spirit and the scope of the disclosure, may be made, by a person skilled in the art. Such modifications, additions, alterations, and improvements should be construed as being within the scope of this disclosure.

LIST OF REFERENCE NUMERALS
1000 – Charging Station / Charging Depot
1100 – Plurality of Charging Modules
1200 – Surveilling and Communication Module
2000 – Centralized Data Collection Member
2001 – Gateway Member
2002 – Internet Cloud
2003 – Distributed Data Collection Center
3000 – Envisaging Member
3200 – Envisaging Module
3400 – EV Simulating Module
4000 – Vehicle Control Unit
5000 – Derating Member
5100 – ESS Surveilling Member
5200 – Estimation Module
5300 – Derating Controller
5400 - Derating Communication Interface
6000 – Energy Module
6100 – Thermal Management System
6200 – Energy Storage System
, Claims:1. A system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, said system comprising:
a charging station (1000) that comprising: a plurality of charging modules (1100); and a surveilling and communication module (1200), said surveilling and communication module (1200) comprising: a surveilling unit and a communication interface, with:
said surveilling unit facilitates surveilling of an at least an environmental parameter of the energy storage system (6200) and the charging station (1000), in real-time, with the surveilled data being transmitted to a centralized data collection member (2000), with the help of the communication interface,
with:
each charging module among the plurality of charging modules (1100) comprising: a charger and a charger communication interface; and
each charging module among the plurality of charging modules (1100) facilitates charging of an electric vehicle independently;
an energy module (6000) that is disposed on the electric vehicle, said energy module (6000) comprising: an energy storage system (6200), and a thermal management system (6100);
a vehicle control unit (4000) that is disposed on the electric vehicle, and facilitates collecting and transmitting a historical trip data of the electric vehicle, and a plurality of vehicle data, in real-time, to the centralized data collection member (2000)
the centralized data collection member (2000) that comprising: an at least one gateway member (2001); an internet cloud (2002); and a distributed data collection center (2003), with:
the real-time data collected from the plurality of charging modules (1100) in the charging station (1000) are transmitted first to an internet cloud (2002) with the help of the at least one gateway member (2001), and finally to a distributed data collection center (2003); and
the data from the distributed data collection center (2003) being transmitted to the plurality of charging modules (1100) with the help of the internet cloud (2002) and the at least one gateway member (2001);
an envisaging member (3000) that comprising: an envisaging module (3200) that is configured to facilitate the envisaging of next trip driving pattern of the electric vehicle; and an EV simulating module (3400) that envisages the required current and voltage, for charging the electric vehicle, to enhance the charging efficiency of the energy storage system (6200) of an electric vehicle, at the charging station (1000); and
a derating member (5000) that is disposed on the electric vehicle, and being associated with the energy module (6000) and the vehicle control unit (4000) to evaluate a derating factor to control the speed of the electric vehicle, while said electric vehicle being coming towards the charging station, said derating member (5000) comprising:
an ESS surveilling unit (5100) that is configured to surveil an at least a parameter of the energy storage system (6200), in real-time, with: the surveilled at least one parameter being transmitted to an estimation module (5200);
the estimation module (5200) that estimates the state of charge (SOC) and ohmic resistance of the energy storage system (6200); and
a derating controller (5300) that collects data from the vehicle control unit (4000) and from the centralized data collection member (2000) with the help of a derating communication interface (5400) and evaluates the derating factor to control the speed of the electric vehicle, with:
said ESS surveilling unit (5100), and said estimation module (5200) are communicatively associated with each other, and are embedded on the derating controller (5300).
2. The system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, as claimed in claim 1, wherein:
the at least one environmental parameter of the energy storage system (6200) and the charging station (1000) includes temperature.
3. The system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, as claimed in claim 1, wherein:
the plurality of vehicle data includes current location, speed, acceleration, and available charge level of the energy storage system.
4. The system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, as claimed in claim 1, wherein: the derating controller (5300) is a microcontroller.
5. The system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, as claimed in claim 1, wherein: the at least one parameter surveilled by ESS surveilling unit (5100) includes voltage, current, and temperature.
6. The system, to enhance the charging efficiency of an energy storage system of an electric vehicle, at a charging station, with reduced thermal management system usage and reduced charging time, as claimed in claim 1, wherein:
the data collected, by the derating controller, from the vehicle control unit (4000) and from the centralized data collection member (2000) includes energy storage system parameters, vehicle speed, vehicle acceleration, and environmental parameter of the charging station (1000).