Claims:1) A method for optimizing the charging of an electric vehicle at a charging station, comprising-

a) Implementing a first sub-process for preventing the overstay of the electric vehicle while being charged from a Type 2 AC charger at the charging station beyond the achievement of a desired level of charge, to therefore make said charging station free for use by other electric vehicles that need to be charged;

b) Optimizing the electrical feed to the electrical vehicle in accordance with the type and condition of the electric vehicle and the battery on-board said electric vehicle; and

c) Altering the electrical feed to the charging station and other charging stations fed from the same grid, in order to optimize the electrical energy allocation between said charging station and other charging stations fed from the same grid.

2) The method for optimizing the charging of an electric vehicle at a charging station as claimed in claim 1, wherein the first sub-process for preventing the overstay of the electric vehicle at the charging station comprises-

a) Measuring in real time, by means of a charge pilot monitoring circuit (02) provisioned within the charging station (01), the charging response time of an electric vehicle received for charging at said charging station (01);

b) Measuring in real time, by means of a charge current monitoring circuit (03) provisioned within the charging station (01), the current per phase being supplied to the electric vehicle received for charging at said charging station (01);

c) Feeding the measurements logged by the charge pilot monitoring circuit (02) and charge current monitoring circuit (03) to a microcontroller (04) to thereby timestamp and communicate the same, in form of a real time over the air message, to a cloud server (05);

d) Comparing, at the cloud server (05), contents of the real time over the air message to self-learning lookup tables pre-provisioned in said cloud server (05), to arrive at a decision opted among:

? Continuing the charging cycle instance, in event of the contents of the real time over the air message being found to be within those in the pre-provisioned lookup tables;

? maximum current prescribed for the specifications and condition of the identity of the electric vehicle, model of said electric vehicle, specifications of the battery in said electric vehicle received for charging;

? Optimizing the charging cycle instance in event of the contents of the real time over the air message being found not to agree with those in the pre-provisioned lookup tables; and

? Stopping the charging cycle instance, in event of the contents of the real time over the air message being found to agree with the maximum values in the pre-provisioned lookup tables.

e) Conveying, from the cloud server (05), the decision opted, in form of a real time over the air message, to-

? The charging station (01) for execution of the decision reached; and

? A smartphone (06) in possession of the driver of the electric vehicle received for charging at said charging station (01), to thus alert said driver of the decision and therefore remove said electric vehicle from said charging station (01) in a timely manner without any overstay.

3) The method for optimizing the charging of an electric vehicle at a charging station as claimed in claim 2, wherein the first sub-process for preventing the overstay of the electric vehicle at the charging station further comprises levying of an overstay penalty in proportion to the overstay, at the charging station, of the electric vehicle beyond the achievement of the desired level of charge.

4) The method for optimizing the charging of an electric vehicle at a charging station as claimed in claim 2, wherein the charge pilot monitoring circuit (02), the charge current monitoring circuit (03), and the microcontroller (04) are provisioned within the charging station (01) as an original component in the event of a new instance of said charging station (01).

5) The method for optimizing the charging of an electric vehicle at a charging station as claimed in claim 2, wherein the charge pilot monitoring circuit (02), the charge current monitoring circuit (03), and the microcontroller (04) are provisioned within the charging station (01) as a retrofit arrangement in the event of a preexisting instance of said charging station (01).

6) The method for optimizing the charging of an electric vehicle at a charging station as claimed in claim 1, wherein altering the electrical feed to the charging station and other charging stations fed from the same grid is implemented by reducing the electrical power allocated for charging stations at which charging has been completed.

7) A system for optimizing the charging of an electric vehicle via a Type 2 AC charger at a charging station, including-

a) electric vehicle supply equipment at the charging station having-

? a charge pilot monitoring circuit (02) to measure signal response timings of the electric vehicle after sending the charger ready signal;

? a charge current monitoring circuit (03) to measure and log the current per phase while charging the electric vehicle;

? microcontroller (04) with embedded software-implemented computational logic programmed for receiving the output signal data of the circuits (02 and 03), time stamping said output signal data and transmitting it in real time, over the air, to a cloud server (05);

b) a cloud server (05), provisioning-

? predefined self-learning lookup tables to allow determination of the identity of the electric vehicle, model of said electric vehicle, specifications of the battery in said electric vehicle received for charging, and response time of said electric vehicle for charging; and

? embedded software-implemented computational logic programmed to receive signal data from the microcontroller (04) to compare the output signal data to standard specifications including response time and current to therefore arrive logically at a decision between continuation, optimization or stopping the charging instance, computing charges to be paid for the completed charging session including the breakup and applicable taxes, and communicating the same in the form of alerts sent, over the air, to a smartphone in possession of the electric vehicle driver;

? embedded software-implemented computational logic programmed to alter the electrical feed to the charging station and other charging stations fed from the same grid is implemented by reducing the electrical power allocated for charging stations at which charging has been completed

c) a downloadable applet (06) for installation on a smartphone of the user of the electric vehicle, for subscribing to interactive communications with the cloud server (05), to thereby allow -

? at the backend while charging of the electric vehicle, reciprocal transaction of data, via the internet in format of push notifications, securely between the smartphone (06) and the cloud server (05);

? at the front end while charging of the electric vehicle, displaying to the user of the electric vehicle via a series of on-screen interfaces, parameter data of the charging process including the charging status, SoC, power used, charging start / elapsed / remaining time, and also rates charged for electricity consumed at the particular charging station (01); and

? Upon charging of the electric vehicle to a level desired by the user of said electric vehicle, displaying to said user of the electric vehicle via a series of on-screen interfaces, the status of charge computation of charges to be paid for the completed charging session including the breakup and applicable taxes as computed by the cloud server (05). , Description:-: Complete Specification :-

“Method and system for predicting the charging state of an electric vehicle and applications thereof”

Field of the invention
This invention relates to the determination and monitoring of RTSoC of an EV while being charged from a Type 2 AC charger, and utilization of this information to optimize and or cease the charging cycle/s of said EV.

Definitions and interpretations
Before undertaking the detailed description of the invention below, it may be advantageous to set forth definitions of certain words or phrases used throughout this patent document: the terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation; the term “or” is inclusive, meaning and/or; the phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean to include, be included within, interconnect, with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like; and the term “SoC” refers State-of-Charge; “RTSoC” refers Real-Time SoC; “EV” refers electric vehicle which is fully or partially propelled by an electric motor and/or otherwise relying for propulsion fully or partially on electrical energy stored in batteries; “Conventional Fuel” refers fossil fuel, including petrol, diesel, compressed / liquefied natural gas and their likes; “R&D” refers research and development; “CCS” refers Combined Charging System; “BMS” refers battery management system; “CP” refers charge pilot; “CSMS” refers Charging Station Management System; “OTA” refers Over the Air communication, by any means chosen among GSM, Ethernet, WiFi, Bluetooth and their likes; “MCU” refers microcontroller unit; “RISC” refers Reduced Instruction Set Computer; “ARM” refers Advanced RISC Machines (as derived from the original originally Acorn RISC Machines); “EVSE” refers electric vehicle supply equipment for transfer of energy between the electric utility power and the EV, being a core component provided at the charging station;

Background of the invention
Rapid depletion of fossil fuel reserves and critical environmental concerns have championed the search for renewable clean fuels, in which electricity has emerged as one of the main contenders for the future of automotive industry. Consequently, the past decade has witnessed great strides in the R&D of EVs with many automobile manufacturers thus switching to the bandwagon of EVs and more specifically affordable EVs, resulting in a viable choice for consumers across the world to migrate away from their Conventional Fuel vehicles.

However mass-adoption of electricity for automotive applications, termed popularly as electric mobility adoption, has not come by easily as it sounds, particularly due to that methodologies for commercially-viable generation of electricity, frugal utilization of electrical energy, and optimizing the intake of electrical energy from the grid for automotive applications has not evolved as fast as R&D towards manufacturing of EVs.

Batteries of EVs can be charged typically, in a plug-in manner, through an external high-voltage charger, such as one provisioned in a charging station or charging kiosk. If electric mobility adoption were to succeed, it shall need to be preceded by establishment of massive charging infrastructure, majorly charging stations, electric feed lines, transformers, switchgear etcetera with high frequency throughout the geography in which such electric mobility adoption is to manifest.

Upgrading the yet-limited charging infrastructure from stand points of capacity, flexibility, power routing and control are undoubtedly very extensive as well as expensive thoroughfares, which may often be technically and / or commercially viable / feasible. Hence, there is a pressing need in the art to optimize the usage of said yet-limited charging infrastructure, particularly by avoiding or at least minimizing its misuse.

To appreciate, the minimum residency of an EV at a charging station or, in other words, the occupancy of charging stations is decided by one or more among several factors including the strength of electric power provided at said charging station or charging kiosk, condition and capacity of the EV battery to be charged, charging specifications (majorly voltage, current, and charging time) prescribed for the EV battery used, safety standards etcetera. The term of occupancy of charging stations by EVs due to these factors is legitimate, and thus defines a fundamental threshold exceeding which any overage amounts to hoarding and misuse of the charging utility.

As can be thus appreciated, “charging overstay” or blocking of charging stations by charged EVs is the commonest underlying reason for underutilization of available charging infrastructure. Extended occupancy of EV charging stations has been attributed the world over to that the drivers of said EVs do not realize that their EV is fully charged and / or they just wish to extend the time for which they can park their EVs at the charging station. This extended occupancy denies a deserved turn for other EVs, whose drivers naturally are turned away from the whole prospect of using EVs.

Thus, there is a pressing need for some way to avoid the extended occupancy by EVs of charging utilities, thus freeing valuable resources while also protecting the batteries of EVs from damage due to anything else than their prescribed charging specifications.

CCS plugs of fast charging stations can read battery SoC, however depend on whether or not the EV advertises / shares this data. Type 2 AC chargers do not have this functionality, hence cannot determine battery SoC. Thus, charging overstay is not rare, and thus a persisting issue that remains to be addressed.

Technical issues to be resolved
On basis of the aforesaid background, the reader may appreciate at least the following technical issues that ought to be resolved-
1) Estimation, from the charger side, of the instantaneous RTSoC of an EV battery;
2) Optimization, in a driver-aware manner, of charging of EV batteries;
3) Stopping, in a driver-aware manner, of charging of EV batteries; and
4) Accuracy and precision, while accommodating all varieties of EV batteries and their charging specifications.

Description of related art
Prior art bears a few scattered references to solutions proposed for meeting the aforesaid wants. Algorithms which stochastically predict the SoC of EV batteries are seen to be proposed, however are inaccurate and inflexible when it comes to RTSoC and the sheer variety of batteries that EVs of today come equipped with.
Prior art, to the extent surveyed, lists some scattered attempts to address the issues mentioned hereinabove. CN101939892B (Assigned to Toyota Motor Corp) mentions a method for estimating charged state of secondary battery; CN103793758B (assigned to the North China Electric Power University) mentions a optimization scheduling method for EV charging stations; DE102014112349B4 (assigned to GM Global Technology Operations LLC) teaches a method for predicting the duration of a future charging process for a vehicle battery; US9026347B2 (Assigned to University of California) describes an apparatus for determining instantaneous state of charge (SOC) for managing a battery in an electric vehicle; and CN201310634900.7A (assigned to State grid Chongqing electric power co electric power research institute) are notable in this line.

The above solutions, however are unable to address the specific issues listed herein above, thereby preserving an acute necessity-to-invent and thus focus area/s for further research by the applicant named herein, who has therefore come up with a truly novel and inventive solution for resolving the aforesaid issues once and for all.

A better understanding of the objects, advantages, features, properties and relationships of the present invention will be obtained from the disclosures to follow which set forth an illustrative preferred embodiment and further alternative embodiments by which the present invention is to be performed.

Objectives of the present invention
The present invention is identified in having certain objectives stated below, of which:

It is a primary objective of the present invention to provide a method and its implementing system for optimum utilization of available infrastructure for charging of EVs.

It is another objective further to those above, to enable accurate determination, from the charger side, of instantaneous RTSoC of an EV battery.

It is another objective further to those above, to enable optimization and / or timely stoppage in charging of EV batteries, so as to not waste any unnecessary electrical power and time for charging as well as ensuring health of the EV batteries.

It is another objective further to those above that the method and its implementing system so provided are not unduly expensive, complex, and / or unwieldy to manufacture, integrate, and operate.

The manner in which the above objectives are achieved, together with other objects and advantages which will become subsequently apparent, reside in the detailed description set forth below in reference to the accompanying drawings and furthermore specifically outlined in the independent claims. Other advantageous embodiments of the invention are specified in the dependent claims.

Brief description of drawings
The present invention is explained herein under with reference to the following drawings, in which:

FIG. 1 is a block diagram showing the application environment of the present invention.

FIG. 2 is a schematic diagram to explain integration of the charge current measurement / monitoring circuit and controller at the charging station, as per the disclosures hereof.

FIG. 3 is a schematic diagram to explain integration of the charge current measurement / monitoring circuit at the charging station, as per the disclosures hereof.

FIG. 4 is a screenshot of a user interface exhibited by the applet on the user’s smart phone during implementation of the present invention.

FIG. 5 is a screenshot of another user interface exhibited by the applet on the user’s smart phone during implementation of the present invention.

FIG. 6 is a screenshot of yet another user interface exhibited by the applet on the user’s smart phone during implementation of the present invention.

FIG. 7 is a screenshot of yet another user interface exhibited by the applet on the user’s smart phone during implementation of the present invention.
FIG. 8 is a schematic drawing to explain one use case of the present invention.

FIG. 9 is a schematic drawing to explain another use case of the present invention.

The above drawings are illustrative of particular examples of the present invention but are not intended to limit the scope thereof. The drawings are not to scale (unless so stated) and are intended for use solely in conjunction with their explanations in the following detailed description to follow. In above drawings, wherever possible, the same references and symbols have been used throughout to refer to the same or similar parts, as under-


(01) - EV charging station
(02) - Charge pilot monitoring circuit
(03) - Charge current monitoring circuit
(04) - Microcontroller
(05) - Cloud server
(06) - Smartphone

Though numbering has been introduced to demarcate reference to specific components in relation to such references being made in different sections of this specification, all components are not shown or numbered in each drawing to avoid obscuring the invention proposed.

Summary / Statement of the present invention
The present inventor proposes to address at least majority of the shortcomings of state-of-art by advantageous incorporation of intelligent circuitry in the EV charger, which is capable of measuring signal response timings and create charge profiles unique for each of the EV models. By comparing these profile coordinates with pre-stored look-up tables (within charge station controller or at an external cloud), the charge station can predict the instantaneous state of charge (SoC) of the battery; further the station / CSMS can inform the EV driver when the desired level of SoC is reached.

Attention of the reader is now requested to the detailed description to follow which narrates a preferred embodiment of the present invention and such other ways in which principles of the invention may be employed without parting from the essence of the invention claimed herein.

Detailed description
The present invention is directed towards a method and circuit arrangement for monitoring or controlling the charging of EV batteries on basis of accurate logging of RTSoC of said EV batteries.

A yet-preferred embodiment of the present invention is directed to an inventive methodology which makes it possible for the determination and monitoring of RTSoC of an EV while being charged from a Type 2 AC charger, and utilization of this information to optimize and or cease the charging cycle/s of said EV.

The present invention primarily focuses on avoiding, or at least minimizing, charging overstays which is a core issue behind underutilization of charging infrastructure available for EVs.

The system architecture of the present invention involves a combination of hardware and software elements which are distributed in the application environment shown in FIG. 1. As seen further in FIG. 2 and FIG. 3, a charge pilot monitoring circuit (02) and charge current monitoring circuit (03) are provisioned within the operative circuit of an EV charging station (01). The circuit (02) is designed to measure signal response timings (as defined in IEC 61851), which is the EV’s response time after sending the charger ready signal. On the other hand, the circuit (03) is designed to measure and log the current per phase while charging the EV.

With continued reference to the FIG. 1-3, it can be seen that the output signals of these circuits (02 and 03) are fed to a microcontroller (04). Build of the microcontroller currently comprises a controller board with atmega328p 8-bit microcontroller based on the enhanced RISC architecture, however a preferred variant shall include a 32-bit STM32 ARM Cortex MCU. The microcontroller (04) contains the embedded software-implemented computational logic to timestamp said output signal data and transmit it in real time, OTA, to a cloud server (05).

With continued reference to the FIG. 1-3, it can be seen that once the time stamped output signal data is received from the EV charging station (01), it is processed at the cloud server (05) to arrive at a real time decision between continuation, optimization or stopping the charging instance, with alerts being sent, OTA, to a smartphone (06) in possession of the EV driver.

According to another aspect herein, in order to enable a human-machine interface, the smartphone (06) and the cloud server (05) are interactively associated via a subscription service which can be availed by the EV user by downloading and installing an applet on his / her smart phone (06). Once installed, this applet (06) manifests a user interface, comprising a series of interactive screens displayed on the screen of the smart phone (06), and at the backend, allows reciprocal transaction of data, via the internet in format of a push notification, securely between the smartphone (06) and the cloud server (05).

The series of interactive screens manifested by the applet (06) can be understood from the accompanying FIG. 4, 5, 6 and 7. Accordingly, key events defining the use case of the present invention are reflected in successive interactive screens manifested by the applet (06) as follows-
a) Upon downloading and installing the applet (06), the user is directed to a registration screen shown in FIG. 5, wherein the EV user is directed to create a signature profile of the EV being used by him / her, by entering the license plate number, EV model and vehicle identification number. This screen may also be later accessed from the settings menu, should the EV user change the EV in use, or needs to select between multiple EVs (and thus correspondingly multiple signature profiles) in use by said EV user. The signature profile/s so inputted are thus advertised and shared between the charging station (01) and the cloud server (05) when an EV comes in for charging;
b) In an instance of charging the EV, the applet (06) is programmed to display a charging status screen shown in FIG. 6, wherein the EV user can read, as updated in real time, parameters of the charging process including the charging status, SoC, power used, charging start / elapsed / remaining time, and also rates charged for electricity consumed at the particular charging station (01); and
c) Upon full / desired charging level being completed, the applet is programmed to take the EV user to a screen shown in FIG. 7 that confirms said status and commercial aspects such as computation of charges to be paid for the completed charging session, its breakup, and regulatory aspects such as applicable taxes (computed / compiled by the cloud server (05)).

Push notifications, as mentioned above are intended to alert the EV user of completion of charging and thus removal of vehicle from the charging station. For this, the charging station (01) is programmed to continuously provide information regarding the charging current for each charging session to the cloud server (05). Based on this information and other data as mentioned above, the embedded software-implemented computational logic provisioned in the cloud server (05) computes the time required and to thus trigger an alert to the user as and when the charging assuming a 100% (or any specific percentage as may be defined by the user using the interface provided by the applet (06) or the charging station (01)). Based on that warning, the EV user has to walk-in to the station and disconnect the vehicle to make space for the next vehicle. Also, when the vehicle is disconnected, the charging station sends a ‘session complete’ message to the backend and the backend may send a thanks message as an acknowledgment.

For the aforesaid processing, decisions and messaging, the cloud server (05) is provisioned with embedded software-implemented computational logic and predefined lookup tables for identification / verification of the identity of the EV being received for charging. The lookup table is self-learning, in the sense the reference values for any EV / model / battery not priorly stored are added whenever such new EV / model / battery are received for the first time at the charging station (01) – hence, over time, the lookup tables become updated and exhaustive as to the EVs / models / batteries available in the market. Data structure of said lookup tables is as exemplarily shown (sample values) in Table 1 below.

EV Model Measured time difference between EVSE ready (PWM 9V) to EV ready (PWM 6V)
A 5.2 seconds
B 4.3 seconds
C 9.2 seconds
D 4.8 seconds
E 3.9 seconds

Table 1

Embedded software-implemented computational logic in the cloud server (05)is programmed to compare the output signal data to standard specifications including response time and current to therefore arrive logically at a decision between continuation, optimization or stopping the charging instance. For this, the present invention considers and discerns between the following five states as shown in FIG.8-
a) State A, when the EV is not connected to the EVSE;
b) State B, when the EV is connected to the EVSE, that is when the EV user plugs the EV in at the charging station and power is available through the EVSE to charge the EV;
c) State C, when the EV is being charged by the EVSE;
d) State D, when the EV is charged and ventilation is required (as defined in the IEC 61851-1); and
e) State E, being of error value due to utility power issues incidental to events including power-cuts or voltage issues.

The aforementioned states are determined based on the input from EV via the CP signal on-CIP circuit in the EVSE, and relayed in real time to the cloud server (05). At the cloud server (05), this data is useful for various purposes, including detecting the difference between and identity of the specific model of EV changed in accordance with the lookup tables provisioned as per the foregoing narration, and accordingly instructing the EVSE, via electronic notification in real time, as to the maximum current prescribed for the specifications and condition of the EV / model / battery received for charging. An exemplary look up table is represented in tables 2 to 5 below.

EV Max Current prescribed
EV A 28.69 A
EV B 16 A
EV C 32 A
EV D 31.6 A
EV E 16 A

Table 2

Sample of same EV Max Current prescribed
EV A Sample1 28.62 A
EV A Sample 2 28.57 A
EV A Sample 3 28.69 A
EV A Sample 4 28.66 A

Table 3

Battery specifications Max Current prescribed
Spec A L1= 28.70 A ; L2=0 A ; L3 = 0A
Spec B L1= 16 A ; L2= 16 A ; L3 = 16A
Spec C L1= 32 A ; L2= 32 A ; L3 = 32 A
Spec D L1= 32 A ; L2= 32 A ; L3 = 32 A
Spec E L1= 16 A ; L2= 16 A ; L3 = 16 A

Table 4

Battery condition Max Current prescribed
Spec A condition 1 L1= 28.70 A ; L2=0 A ; L3 = 0 A
Spec A condition 2 L1= 28.68 A ; L2=0 A ; L3 = 0 A
Spec A condition 3 L1= 28.63 A ; L2=0 A ; L3 = 0 A
Spec A condition 4 L1= 28.55 A ; L2=0 A ; L3 = 0 A

Table 5

The present invention also intends on logic within the cloud server (05) for optimizing the use / delivery of utility power to the charging stations. For example, if there is a cluster of charging stations in a geographical site and the system has determined, that one EV has already reached maximum or desired charging level, then less power is allocated for that particular charging station, or even delivery of power can be ceased to the charging socket even if the EV is still connected to the EVSE, which power can then be routed / allocated for other charging stations in the same geographical site or to charging stations in line to the same electrical feed to charge the EVs faster.

The present invention also intends on behavioral modification of EV drivers, by inclusion of deterrent policies. For example, the charging network provider can instill an additional ‘overstay’ charge / penalty, if the EV driver doesn’t unplug the vehicle even after alerting 85% SoC.

Industrial applicability
The present invention has been reduced to practice by the applicant named herein in a demonstrable manner as outlined in the following studies wherein scenarios in which the present invention is or not implemented are compared head to head in a few sample use cases for appreciating the utility of the present invention-
a) With reference to the accompanying FIG. 8, it can be seen that in a first sample use case of the present invention, it is determined as to what type of vehicle is connected and it’s current battery SoC. When the optimal SOC level of the vehicle is reached, notify EV driver via mobile app/SMS to unplug the vehicle to free-up the charging station for the next vehicle. And/or impose overstay penalty.

Thus in this exemplary use case, when optimal charging conditions exceed (E.g: > 95% SoC), the system notifies the EV driver via mobile app/SMS to unplug the vehicle to free-up the charging station for the next vehicle and/ or impose overstay penalty.

On the other hand, in the conventional scenario wherein the present invention is not deployed, it will not be possible to determine when the optimal charging conditions are met; some of the vehicles continue to draw a very minimum current even if they exceed 98% SoC. So the charging station/management system will consider that the charging is still happening and keep the current session active. And the other vehicles will start queueing up for plugging in next.

b) With reference to the accompanying FIG. 9, it can be seen that in a another sample use case of the present invention, when optimal charging conditions exceed (E.g: > 95% SoC), system notifies the EV driver; terminate the session from backend; and use the allocated power to another station on the same location.

The foregoing description will be regarded as illustrative in nature and not as restrictive in any form whatsoever. Modifications and variations of the system and apparatus described herein will be obvious to those skilled in the art. Such modifications and variations are intended to come within ambit of the present invention, which is limited only by the appended claims.