TECHNICAL FIELD
[001] The present subject matter relates, in general, to electric vehicles and,
in particular, to electric vehicle charging.
5 BACKGROUND
[002] The advancement of technology in the field of automobile industry has
not only improved human lives but has also enabled efficient and safe transportation.
With the increasing demand of oil and increasing air pollution, an increased focus is
on renewable energy and alternative vehicles that can provide a reliable mode of
10 transportation. Electric vehicles (EVs) use motors for propulsion, instead of the
common internal combustion engine. EVs include, but are not limited to, road and rail
vehicles, aircrafts, spacecrafts and underwater vessels. EVs store electricity in an
energy storing device, such as a battery, which can be charged from time to time. EVs
produce no emissions, have less maintenance costs and provide ease of operation. Also,
15 advances in technologies such as storage cell design, braking regeneration, and motor
efficiency have made electric vehicles a viable alternative to vehicles powered by
internal combustion engines.
BRIEF DESCRIPTION OF DRAWINGS
20 [003] The detailed description is described with reference to the
accompanying figures. In the figures, the left-most digit(s) of a reference number
identifies the figure in which the reference number first appears. The same numbers
are used throughout the drawings to reference like features and components.
[004] Figure 1 shows a network environment implemented for electrical
25 vehicle (EV) charging, in accordance with an embodiment of the present subject
matter.
[005] Figure 2 illustrates a battery management system for an EV, according
to an implementation of the present subject matter.
3
[006] Figure 3 shows a charging management terminal for managing charging
of EVs, according to an embodiment of the present subject matter.
[007] Figure 4 illustrates a method for managing charging of EVs, in
accordance with an implementation of the present subject matter.
5 [008] Figure 5 depicts a method of receiving charging order for EVs, in
accordance with an implementation of the present subject matter.
DETAILED DESCRIPTION
[009] Electric vehicles (EVs) are commonly powered by on-board battery
10 packs. Battery packs generally include multiple batteries to store charge, that is used to
drive the EVs. During operation of the EVs, the battery packs lose their stored charge
and have to be recharged. Further, the storage capability of an on-board battery packs
used in the EVs is limited owing to different limitations, such as available space and
allowable weight. Such constrains are often dictated by design of the EVs. For
15 example, in case of e-rickshaws, space for the battery may be constrained to allow more
space for passengers. Consequently, EVs have a limited range of travel and have to be
recharged frequently, for instance, on a daily basis, if not more frequently.
[0010] Electric charging stations are provided to supply electric energy to EVs
for the recharging of battery packs. While some charging stations can be installed at
20 local premise of users, public charging stations are also provided to support recharging
of EVs during transit. Public transport EVs, such as e-busses, e-rikshaws and e-scooters
rely on public charging stations to get their battery packs recharged. Public charging
stations can be used by EV owners on payment of fees in proportion to consumption
of the electricity or duration of charging.
25 [0011] Drivers of public EVs, such as the e-rikshaws, generally drive the EV
from one location to another, during their daily engagements. Sometimes, the energy
stored in battery pack of the EV drops below a threshold value while the EV is in
operation and the EV is to be recharged. In such situations, it becomes difficult for the
4
driver to locate a nearby charging station. Moreover, charging stations in the vicinity
can be congested and the driver may have to wait for long durations to get the EV
recharged. Therefore, identifying an available charging station in a nearby vicinity of
an EV, especially when in an unknow vicinity is difficult for EV drivers.
5 [0012] According to examples of the present subject matter, techniques of EV
charging are described. In an example of the present subject matter, the described
techniques allow determination of information for charging the EV at a charging station
based on various operating factors.
[0013] Determination of whether an EV requires recharging is based on the
10 level of charge available in the battery pack. In an example, during travel or operation
of the EV, the charge level of the battery pack of the EV may be monitored. The charge
of the battery pack of the EV may deplete with time and the depletion of charge may
vary depending of various factors, such as duration of use of the EV, load of EV during
operation, type of peripherals utilized during operation, temperature of operation of the
15 EV, driving behavior of the driver, terrain on which the EV is utilized, etc. Thus,
depending on such factors, sometimes the charge of the battery pack may last for one
day, while in other situations, the charge may deplete earlier. When the charge level of
the battery pack is determined to be below a threshold value, it is identified that the EV
requires recharging of the battery pack.
20 [0014] In an example, along with the charge level of the battery packs,
geographic location of the EV may also be identified. The geographic location of the
EV may be identified based on various known techniques, such as through use of
Global Positioning System (GPS), triangulation through mobile towers, assisted GPS
(A-GPS), and the like. Upon identification of the geographic location of the EV, one
25 or more charging stations in the vicinity of the geographic location of the EV may be
identified. For example, charging stations within 2-3 Kilometer (Km) radius of the
geographic location of the EV may be identified. It would be noted that the vicinity
within which the charging stations are determined may depend on the charge left in the
5
battery pack of the EV. For example, if the charge remaining in the EV can allow the
EV to travel to about 10 Kms, charging stations within a radius of 7-8 Kms may be
identified.
[0015] Further, in another example of the present subject matter, from amongst
5 the charging stations identified within the vicinity of the geographic location of the EV,
an optimum charging station may be identified for charging the EV. The identification
of the optimum charging station for the EV may depend of various factors that may
include, but are not limited to, distance between the geographic location of the EV and
the charging stations, amount of charge left in the EV, current congestion at the
10 charging station or availability of the charging ports at the charging station, traffic
congestion between the geographic location of the EV and the charging station, ease
of reaching to the charging station, charging capabilities of the charging station, offers
available at the charging station, fee of charging levied by the charging station, and
driver categorization.
15 [0016] Thus, a variety of parameters, such as the ones described above may be
used independently or in any combination to identify the optimum charging station.
Further, in an example of the present subject matter, it is possible that each of the
factors may be assigned a weightage. In an example, driver categorization may also be
assigned a weightage for determination of the optimum charging station.
20 [0017] The driver categorization may be indicative of driving behavior of the
driver. In an example, driver categorization ‘A’ may indicate a driving behavior that is
better than a driver categorization ‘B’. In another example, driver categorizations, such
as driver categorization ‘1’, driver categorization ‘2’, ……………, driver
categorization ‘n’ may exist where each driver categorization is indicative of a ranking
25 provided to the driver of the EV based on the driving behavior of the driver.
[0018] In an example, for determining the driver categorization for a driver of
an EV, the driving behavior may be monitored over a predefined period of time. The
driving behavior may be determined based on various operational parameters of the
6
EV, where the various operational parameters are determined by monitoring the usage
of the EV over a period of time. For instance, speed of the EV may be monitored
continuously to identify the instances when the driver over sped. More than a
predefined number of instances of over speeding over a predefined period of time may
5 be indicate of a poor driving behavior. In another example, erratic driving actions, such
as lane changing without activating a turn indicator may also be used together with the
instances of over speeding to determine the driving behavior. In yet another example,
information regarding any traffic violations and accidents that the driver may have been
involved in may also be accounted for determination of the driver behavior and the
10 driver categorization.
[0019] Accordingly, based on the determined driving behavior, the driver may
be assigned a driver categorization. The drivers with similar driving behavior may be
assigned a same driver categorization.
[0020] In an example implementation, certain charging stations may only be
15 provided to drivers who have been categorized in top categories based on their driving
behavior. For example, drivers with driving behavior better than others, may be
assigned a nearer charging station or preferable time slot for charging at a charging
station for their respective EVs. Therefore, the determination of the optimum charging
station may also be based on the category into which driver of the EV has been
20 classified into.
[0021] In an example of the present subject matter, once the optimum charging
stations are identified for the EV, a charging order may be issued to the EV, indicating
a time slot and choice of charging station to be utilized for charging of the EV.
[0022] The present described techniques thus allow for timely and effective
25 charging of the EVs, even in situations where driver of the EVs are unaware of nearby
charging stations. Moreover, since the selection of the charging stations is based on
various factors, an optimum charging station may be chosen effectively for the
recharging of the EV.
7
[0023] While embodiments of the present invention have been described in
context of an e-rickshaw, it will be understood that the same is only to provide an
example of implementation of the present invention and is not be construed as a
limitation. The teachings of the present invention may be extended to other EVs as
5 applicable.
[0024] The above and other features, aspects, and advantages of the subject
matter will be better explained with regard to the following description and
accompanying figures. It should be noted that the description and figures merely
illustrate the principles of the present subject matter along with examples described
10 herein and, should not be construed as a limitation to the present subject matter. It is
thus understood that various arrangements may be devised that, although not explicitly
described or shown herein, embody the principles of the present disclosure. Moreover,
all statements herein reciting principles, aspects, and examples thereof, are intended to
encompass equivalents thereof. Further, for the sake of simplicity, and without
15 limitation, the same numbers are used throughout the drawings to reference like
features and components.
[0025] Figure 1 illustrates a network environment 100 implemented for EV
charging, in accordance with an embodiment of the present subject matter. In an
example of the present subject matter, the environment 100 includes multiple EVs,
20 such as EVs 102-1 and 102-2. The EVs 102-1 and 102-2 may be communicatively
connected to an electric vehicle management system (EVMS) 104 through a network
106.
[0026] In an example, the EVs 102-1 and 102-2 may be e-rickshaws, emotorbikes or any other EVs that may have battery packs and may need to charge the
25 battery packs from time to time by connecting to a charging station. Further, the EVs
102-1 and 102-2 may also include hybrid vehicles that are powered not only by battery
packs but are also powered by oil. However, such hybrid vehicles may also require
recharging of battery packs and may connect to the EVMS 104 for effective charging.
8
Fir the ease of reference, the EVs 102-2 and 102-2 have been commonly referred to as
EVs 102, hereinafter. Further, although two EV 102 have been depicted in the network
environment 100, it would be noted that the multiple such EVs may ply on roads and
may be connected to the EVMS 104 through the network 106.
5 [0027] In an example of the present subject matter, the EVMS 104 may be
implemented as any known computing, such as a rack server, a blade server, a
mainframe computer, a desktop, a personal computer, a notebook or portable computer,
a workstation, and a laptop. Further, in one example, the EVMS 104 may be a
distributed or centralized network system in which different computing devices may
10 host one or more of the hardware or software components of the EVMS 102. It would
be noted that the EVMS 102 may either operate remotely or lie within the vicinity of
the EVs.
[0028] The network 106 may be a single network or a combination of multiple
networks and may use a variety of different communication protocols. The network
15 106 may be a wireless or a wired network, or a combination thereof. Examples of such
individual networks include, but are not limited to, Global System for Mobile
Communication (GSM) network, Universal Mobile Telecommunications System
(UMTS) network, Personal Communications Service (PCS) network, Time Division
Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network,
20 Next Generation Network (NON), Public Switched Telephone Network (PSTN).
Depending on the technology, the network 106 includes various network entities, such
as gateways, routers; however, such details have been omitted for the sake of brevity
of the present description.
[0029] In an example of the present subject matter, the EVMS 104 may
25 determine an optimum charging station for recharging of EVs 102 based on
consideration of various factors. The various factors may be stored in a database 108,
communicatively coupled to the EVMS 104. The database 108 may either be
9
implemented within the EVMS 104 as an internal database or may be implemented as
outside EVMS 104 as an external database.
[0030] The network environment 100 may further include charging stations
110-1, 110-2, …, 110-n to recharge battery packs of the EVs 102. In an example of the
5 present subject matter, the charging stations are communicatively connected to the
EVMS 104 through the network 106. For the ease of reference, the charging
stations110-1, 110-2, …, 110-n have been commonly referred to as charging stations
110, hereinafter.
[0031] In an example of the present subject matter, the charging stations 110
10 connected through the network 106 may support different payment methods, such as
ChargePoint, Blink, Greenlots, eVgo, Aerovironment, Azra, SemaConnect, Circuit
Électrique, RéseauVer, Sun Country Highway, BHIM, Bharat QR and Unified
Payment Interface (UPI). Further, depending on the charging station, different rates of
charging may apply, that may vary include session/monthly/yearly charges or flat
15 charges. Some charging stations 110 may also provide free energy to charge the battery
packs of the EVs 102.
[0032] The EVs 102 may include, apart from other things, a battery
management system (BMS) 112, one or more battery packs 114, at least one charging
connector 116, and a sensor assembly118.
20 [0033] In an example, the BMS 112 may monitor and control the utilization
and charging of the battery packs 114. Further, the BMS 112 may also communicate
with the charging connector 116 to control charging of the battery packs 114.
Therefore, the BMS 112 can be understood to act as a control terminal of the battery
packs 114. Among other functions, the BMS 112 also manages battery pack functions,
25 such as monitoring current battery pack charge level, ensuring low consumption of the
battery packs when in inactive mode, prevention from overcharging and under
discharge. For the purpose of managing the battery functions, the BMS 112 measures
10
various parameters of the battery packs 114, such as battery cell voltage, temperature,
etc.
[0034] In another example of the present subject matter, the BMS 112 may also
communicate with the sensor assembly 118 to receive various operational parameters
5 of the EV 102. In an example, the BMS 112 may receive parameters, such as speed or
location of the EV 102. Further, the sensor assembly 118 may include multiple sensors
to monitor and gather data corresponding to various parameters of the EV 102.
[0035] In an example of the present subject matter, the battery packs 114 may
include lithium ion batteries. Other examples of the battery pack 114 may include,
10 nickel metal hydride batteries, graphene batteries, cadmium batteries, sodium or zebra
batteries. Dur to their utility and advantages over other types of batteries, lithium ion
batteries, may be used in the EVs 102. A typical lithium ion battery cell yields 80-90%
of discharge efficiency. Examples of the types of lithium ion batteries that can be
incorporated in the EVs 102 can be NCA, NMC, LMO, and LifePO4.
15 [0036] The EVs 102 includes a charging connector 116. The charging
connector 116 may be understood to be an input terminal to receive power and charge
the battery packs 114. Examples of the charging connector 116 include but are not
limited to mode 2, mode 3 charger or a plug type 1, or type 2. In accordance with an
example embodiment of the present subject matter, the charging connector 116 may
20 function in response to instructions given by a BMS 112.
[0037] The functioning of the BMS 112 and the EVMS 104 to providing
effective charging to the EVs 102 is further described in reference to forthcoming
figures.
[0038] Figure 2 illustrates a battery management system (BMS) 112 for an EV,
25 according to an implementation of the present subject matter. In an example of the
present subject matter, the BMS 112 includes an interaction engine 202, a control
engine 204 and a data store 206. As described earlier the BMS may act as a control to
the battery packs 114 of the EV 102 and may communicate with other elements of the
11
EV 102, such as sensor assembly 118 (not shown) and charging connector 116 (not
shown).
[0039] In an example, the interaction engine 202 of the BMS 112 may facilitate
communication between the BMS 112 and the sensor assembly 118 and charging
5 connector 116. Further, the interaction engine 202 may also facilitate communication
between the BMS 112 and the EVMS 104. The communication may typically be based
on known communication protocols. The interaction engine 202 may use several
methods of serial or parallel communication, for instance and not limited to, CAN bus
communication, which is commonly used in automotive environments, DC-BUS for
10 serial communication, and different types of wireless communication. The
communication protocols can vary as per the hardware implementation.
[0040] The interaction engine 202 communicates internally with various
sensors of the sensor assembly 118 (not shown) that may be installed on the EVs 102
and transmits the inputs obtained from the sensors to the EVMS 104. Based on the
15 inputs obtained from the sensor assembly 118 and other battery information
communicated by the interaction engine 202 to the EVMS 104, the EVMS 104
provides control information to the control engine 204 of the BMS 112 to take actions
to control the battery packs 114 and in turn the operation of the EVs 102. For example,
the interaction engine 202 may receive charging orders from the EVMS 104 and may
20 provide such charging orders to the control engine 204.
[0041] The control engine 204 may control the functioning of the battery packs
114 of the EV 102. For example, the control engine 204 may be responsible for
controlling the trigger signals to the charging connector which may determine charging
of the battery packs 114. In an example implementation, the control engine 204 controls
25 the charging of the battery packs 114 as per predefined rule. The control engine 204
instructs the charging connector 116 (not shown) of the EVs 102 to either connect to
the supply terminals of the charging station 110 (not shown) or stop the charging
process. The control engine 204 also controls the charging schedule for the vehicle by
12
ensuring the charging is done as per the charging orders received from the EVMS 104.
The control engine 204 also ensures that the charging of the battery packs 114 is in
accordance with instructions provided by the EVMS 104, if any. For example, if the
EVMS 104 determines a rate of charging for the battery packs 114, the control engine
5 204 ensures that the battery packs 114 charge at the specified rate by controlling the
charging connecter 116 accordingly.
[0042] In the present description, the engine(s) may be implemented as a
combination of hardware and programming (for example, programmable instructions)
to implement certain functionalities of the engine(s), such as transmitting signals. In
10 examples described herein, such combinations of hardware and programming may be
implemented in several different ways. For example, engine(s) may be implemented
by electronic circuitry.
[0043] In an example implementation, the data store 206 may be understood as
a memory component to store various data collated, manipulated or otherwise used by
15 the BMS 112 in its operation. The memory component may include any computerreadable medium including, for example, volatile memory (e.g., RAM), and/or nonvolatile memory (e.g., EEPROM, flash memory, etc.).
[0044] The data store 206 may store information, for example and not limited
to, inputs obtained from the sensor assembly 118 installed on the EVs 102, such as EV
20 geographic location or current charge level information. The data store 206 may also
store instructions communicated to the BMS 112 by the EVMS 104, such as charging
orders. Other examples of information that the data store 206 may store are: customer
rating in case of an electric rickshaw, battery maintenance data, drivers credit
information, driver’s history information, information regarding driving actions.
25 [0045] Figure 3 schematically depicts various components of an electric
vehicle management system (EVMS) 104, according to an example of the present
subject matter.
13
[0046] The EVMS 104, among other things, includes processor(s) 302 and
memory 304 and interface(s) 306 coupled to the processor(s) 302. The processor(s)
302 may be implemented as microprocessors, microcomputers, microcontrollers,
digital signal processors, central processing units, state machines, logic circuitries,
5 and/or any devices that manipulate signals based on operational instructions. Among
other capabilities, the processor(s) 302 is configured to fetch and execute computerreadable instructions stored in a memory 304 of the EVMS 104. The memory 304 may
include any computer-readable medium including, for example, volatile memory (e.g.,
RAM), and/or non-volatile memory (e.g., EEPROM, flash memory, etc.).
10 [0047] The functions of the various elements shown in the Figures, including
any functional blocks labelled as “processor(s)”, may be provided through the use of
dedicated hardware as well as hardware capable of executing software. When provided
by a processor, the functions may be provided by a single dedicated processor, by a
single shared processor, or by a plurality of individual processors, some of which may
15 be shared. Moreover, explicit use of the term “processor” should not be construed to
refer exclusively to hardware capable of executing software, and may implicitly
include, without limitation, digital signal processor (DSP) hardware, network
processor, application specific integrated circuit (ASIC), field programmable gate
array (FPGA), read only memory (ROM) for storing software, random access memory
20 (RAM), non-volatile storage. Other hardware, conventional and/or custom, may also
be included.
[0048] The interface(s) 306 may include a variety of software and hardware
interfaces that allow the EVMS 104 to interact with BMS 112 of one or more EVs 102.
In an example of the present subject matter, the EVMS 104 may further include engines
25 308 and data 310. The engines 308 may either be implemented within the EVMS 104
in the memory 304, or may reside in an external database, such as database 108 (not
shown). The engines 308 include routines, programs, objects, components, data
14
structures, and the like, which perform particular tasks or implement particular abstract
data types.
[0049] In an example of the present subject matter, the engines 308 may include
an analysis engine 312, a communication engine 314, and other engines 316. The
5 communication engine 314 may allow the EVMS 104 to communicate with the EVs
102 and its components, such as BMS 112, and charging stations 110. Further, the
analysis engine 312 may analyze different factors and data provided by the BMS 112
to determine charging order to the EVs 102.
[0050] In operation, the communication engine 314 of the EVMS 104 may
10 communicate with the BMS 112 of the EVs 102 to receive different data, such as
battery charge information, location of the EVs 102, battery usage patterns, and driver
behavior. The communication engine 314 may further communicate with the charging
stations 110 to receive data, such as current congestion at the charging station or
availability of the charging ports at the charging station, charging capabilities of the
15 charging station, offers available at the charging station, fee of charging levied by the
charging station, and their respective locations. Further, the analysis engine 316 may
analyze different parameters received from the EVs 102 and the charging stations 110
along with different factors, such as distance between the geographic location of the
EV and the charging stations, amount of charge left in the EV, traffic congestion
20 between the geographic location of the EV and the charging station, ease of reaching
to the charging station, and driver categorization to determine an optimum charging
station for the EVs 102.
[0051] In an example, the analysis engine 312 may determine the driver
categorization for a driver of an EV based on the driving behavior monitored over a
25 predefined period of time. The driving behavior may be determined based on various
operational parameters of the EV, where the various operational parameters are
determined by monitoring the usage of the EV over a period of time. For instance,
speed of the EV may be monitored continuously to identify the instances when the
15
driver over sped. More than a predefined number of instances of over speeding over a
predefined period of time may be indicate of a poor driving behavior. In another
example, erratic driving actions, such as lane changing without activating a turn
indicator may also be used together with the instances of over speeding to determine
5 the driving behavior. In yet another example, information regarding any traffic
violations and accidents that the driver may have been involved in may also be
accounted for determination of the driver behavior.
[0052] Accordingly, based on the determined driving behavior, the analysis
engine 312 may assign a driver, a driver categorization. The drivers with similar driving
10 behavior may be assigned a same driver categorization. In an example of the present
subject matter, the analysis engine 316 may generate a charging order for EVs 102 with
charge level less than a threshold and may transmit the charging order to the BMS 112
of the EVs 102, through the communication engine 314. The charging order may
provide information for charging the EVs 102 at the optimum charging station, where
15 the information may include details of the optimum charging station and an available
time slot available for charging the EVs 102 at the optimum charging station. It would
be noted that the optimum charging station may control a charging schedule of the EVs
102 by enabling the charging to be done only at the available time slot.
[0053] In an example, the engines 308 may also include other engines 316 that
20 supplement functions of the EVMS 104. The data 310 serves, amongst other things, as
a repository for storing data that may be fetched, processed, received, or generated by
the engines 308. The data 310 comprises data provided by the BMS 112, such as battery
charge data 318, EV location data 320, charging station data 322, driver categorization
data 324, and other data 326 corresponding to the other engines 316.
25 [0054] Figure 4 and 5 illustrate methods 400 and 500 for managing charging
of EVs, in accordance with an implementation of the present subject matter. Although
the methods 400 and 500 may be implemented in a variety of EVs, for the ease of
explanation, the present description of the example methods 400 and 500 of managing
16
charging of EVs is provided in reference to e-rickshaws. Also, although the methods
400 and 500 may be implemented in a variety of computing devices, but for the ease
of explanation, the present description of the example methods 400 and 500 for
managing charging of EVs is provided in reference to the above-described BMS 112
5 and EVMS 104.
[0055] The order in which the methods 400 and 500 are described is not
intended to be construed as a limitation, and any number of the described method
blocks may be combined in any order to implement the methods 400 and 500, or any
alternative methods. Furthermore, the methods 400 and 500 may be implemented by
10 processor(s) or computing device(s) through any suitable hardware, non-transitory
machine-readable instructions, or combination thereof.
[0056] It may be understood that blocks of the methods 400 and 500 may be
performed by programmed computing devices. The blocks of the methods 400 and 500
may be executed based on instructions stored in a non-transitory computer-readable
15 medium, as will be readily understood. The non-transitory computer-readable medium
may include, for example, digital memories, magnetic storage media, such as magnetic
disks and magnetic tapes, hard drives, or optically readable digital data storage media.
[0057] Referring to Figure 4, at block 402 charge level of the battery pack of
an electric vehicle is determined. The charge of the battery packs of an EV may change
20 from time to time and the availability of remaining charge in the battery packs of the
EV may be ascertained regularly. In an example of the present subject matter, the BMS
112 of the EV may regularly determine the charge level of battery packs 114.
[0058] At block 404, it is determined if the charge level of the battery pack
below a threshold value. If the charge level of the battery packs in the EV is not below
25 the threshold value, the control of the decision block 404 flows to block 402 and the
charge level of the battery packs is again determined. However, if the charge level of
the battery packs in the EV is below the threshold value, the control of the decision
block 404 flows to block 406.
17
[0059] At block 406, geographic location of the EV is determined. In an
example, the geographic location of the EV may be determined based on known
techniques, such as through use of Global Positioning System (GPS), triangulation
through mobile towers, assisted GPS (A-GPS), and the like.
5 [0060] At block 408, one or more charging station(s) within the predefined area
from the geographic location of the EV are identified. The determination of the
charging stations maybe made based on the charge level of the battery packs along with
the geographic location of the EV.
[0061] At block 410, an optimum charging station from the one or more
10 charging stations is determined. In an example of the present subject matter, the
determination may further be based on factors, such as distance between the geographic
location of the EV and the charging stations, current congestion at the charging station
or availability of the charging ports at the charging station, traffic congestion between
the geographic location of the EV and the charging station, ease of reaching to the
15 charging station, charging capabilities of the charging station, offers available at the
charging station, fee of charging levied by the charging station, and driver
categorization.
[0062] At block 412, a charging order is issued to the electric vehicle. In an
example of the present subject matter, the charging order may provide information for
20 charging the EV at the optimum charging station, where the information may include
details of the optimum charging station and an available time slot for charging the EV
at the optimum charging station. In said example, the optimum charging station may
control a charging schedule of the EV by enabling the charging to be done only at the
available time slot.
25 [0063] Referring to Fig. 5, method for receiving a charging order, for effective
charging of battery packs of the EV is described. At block 502, charge level of the
battery packs of the electric vehicle is determined. In an example of the present subject
matter, the BMS 112 may determine the charge level of the battery packs of the EV.
18
[0064] At block 504, geographic location of the electric vehicle is determined.
The geographic location of the electric vehicle may be determined based on known
techniques of determining location, such as through use of Global Positioning System
(GPS), triangulation through mobile towers, assisted GPS (A-GPS), and the like.
5 [0065] At block 506, the charge level of the battery packs and the geographic
location of the electric vehicle is communicated. In an example of the present subject
matter, the charge level and the geographic location of the electric vehicle is
communicated to a server, or a central electric vehicle management system, such as
EVMS 104. Further, in an example, various other parameters of the electric vehicle,
10 such as battery usage pattern, driving patterns of the driver, speed, average distance
travelled, and travelling pattern of the electric vehicle may also be communicated to
the EVMS 104.
[0066] At block 510, a charging order for the charging of the battery packs of
the electric vehicle is received. In an example of the present subject matter, the
15 charging order is provided by the EVMS 104. The charging order for the electric
vehicle may include details of an optimum charging station which may be utilized for
charging the electric vehicle, along with an available time slot for charging the EV at
the optimum charging station. The charging station may be determined by the EVMS
104 based on consideration of different factors, such as distance between the
20 geographic location of the EV and the charging stations, amount of charge left in the
EV, current congestion at the charging station or availability of the charging ports at
the charging station, traffic congestion between the geographic location of the EV and
the charging station, ease of reaching to the charging station, charging capabilities of
the charging station, offers available at the charging station, fee of charging levied by
25 the charging station, and driver categorization.
[0067] Although the subject matter has been described in considerable detail
with reference to certain examples and implementations thereof, other implementations
19
are possible. As such, the present disclosure should not be considered limited to the
description of the preferred examples and implementations contained therein.
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I/We Claim:
1. A method for managing charging of an electric vehicle (EV), the method
comprising:
receiving a charge level of at least one battery pack of the EV;
5 determining the charge level of the at least one battery pack to be below a
threshold value;
receiving a geographic location of the EV;
identifying a plurality of charging stations based on the geographic location of
the EV and the charge level of the at least one battery pack; and
10 issuing a charging order for the EV, wherein the charging order is indicative of
information for charging the EV at a charging station from amongst the plurality of
charging stations.
2. The method as claimed in claim 1, wherein the information for charging the EV
15 comprises the details of the charging station and an available time slot for charging the
EV at the charging station.
3. The method as claimed in claim 2, further comprising controlling a charging
schedule of the EV by enabling the charging to be done at the available time slot.
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4. The method as claimed in claim 1, wherein the charging station is assigned based
at least one of distance between the geographic location of the EV and the plurality of
charging stations, congestion at the charging station, charging capabilities of the
plurality of charging stations, traffic congestion between the geographic location of the
25 EV and the plurality of charging stations, offers available at the plurality of charging
stations, and fee of charging levied by the plurality of charging stations.
5. The method as claimed in claim 1, further comprising:
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receiving operational parameters associated with the EV, wherein the operational
parameters are indicative of usage of the EV;
receiving information indicating traffic violations and accidents done by the
driver; and
5 determining a driver categorization based on the operational parameters
associated with the EV and the information indicating traffic violations and accidents
done by the driver, wherein the driver categorization is indicative of driving behaviour
of a driver of the EV.
10 6. The method as claimed in claim 4, further comprising assigning the charging
station based on the driver categorization.
7. The method as claimed in claim 6, further comprising assigning the charging
station at a shorter distance for a driver having placed in a higher category of driver
15 categorization with respect to other drivers.
8. An electric vehicle management system (EVMS), the EVMS comprising:
a communication engine to receive information indicating a charge level of at
least one battery pack of an electric vehicle (EV) and a geographic location of the EV;
20 and
an analysis engine coupled to the communication engine to:
determine the charge level of the at least one battery pack to be below a
threshold value;
identify a plurality of charging stations based on the charge level of the at
25 least one battery pack and the geographic location of the EV; and
issue a charging order for the EV, wherein the charging order is indicative
of information for charging the EV at a charging station from amongst the
plurality of charging stations.
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9. The EVMS as claimed in claim 8, wherein the analysis engine is to assign the
charging station based on at least one of distance between the geographic location of
the EV and the plurality of charging stations, congestion at the charging station,
5 charging capabilities of the plurality of charging stations, traffic congestion between
the geographic location of the EV and the plurality of charging stations, offers available
at the plurality of charging stations, and fee of charging levied by the plurality of
charging stations.
10 10. The EVMS as claimed in claim 8, wherein the communication engine is to
further:
receive operational parameters associated with the EV, wherein the operational
parameters are indicative of usage of the EV; and
receive information indicating traffic violations and accidents done by the driver.
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11. The EVMS as claimed in claim 10, wherein the analysis engine is to:
determine a driver categorization based on the operational parameters and
information indicating traffic violations and accidents done by the driver, wherein the
driver categorization is indicative of driving behaviour of a driver of the EV; and
20 assign the charging station from amongst the plurality of charging stations based
on the driver categorization.
12. The EVMS as claimed in claim 11, wherein the analysis engine is to assign the
charging station at a shorter distance for a driver having a higher category of the driver
25 categorization with respect to other drivers.
13. An electric vehicle (EV) comprising:
a charging connector;
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at least one battery pack coupled to the charging connector;
a batter management system (BMS) coupled to the at least one battery pack, the
BMS comprising:
an interaction engine to transmit information indicating a charge level of
5 the at least one battery pack of the EV and a geographic location of the EV; and
a control engine coupled to the communication engine to receive a charging
order for the EV, wherein the charging order is indicative of information for
charging the EV at a charging station from amongst a plurality of the charging
stations available within a predefined area from the geographic location of the
10 EV.
14. The EV as claimed in claim 13, wherein the EV further comprises a sensor
assembly coupled to the BMS, wherein the sensor assembly is to determine operational
parameters associated with the EV, wherein the operational parameters are indicative
15 of usage of the EV.
15. The EV as claimed in claim 14, wherein the interaction engine is to further
transmit the operational parameters associated with the EV.