TECHNICAL FIELD
[001] The present subject matter relates, in general, to electric vehicles and,
in particular, to charging of electric vehicles.
5
BACKGROUND
[002] With progressive exhaustion of fossil fuels, such as gasoline and the
enhanced awareness of environmental protection, more attention is being paid to
electric vehicles. Fueling the electric vehicles with electricity offers advantages, such
10 as negligible emission which is not available in conventional internal combustion
engine vehicles. Other advantages of electrically powered vehicles include reduction
in noise of operation of the vehicle. Electric vehicles, interchangeably referred to as
EVs, have also gained popularity as their usage involves a onetime investment thereby
providing maximum cost effectiveness.
15 [003] An electric vehicle includes a battery that powers the vehicle. The
battery is recharged from time to time by connecting the battery to a charging station,
for example, using a charger. Generally, the storage capability of an on-board battery
used in the electric vehicle is limited owing to limitations, such as space and weight
constrains dictated by design of the electric vehicle. Consequently, the electric vehicles
20 need to be recharged frequently, for instance, on a daily basis, if not more frequently.
BRIEF DESCRIPTION OF DRAWINGS
[004] The detailed description is described with reference to the
accompanying figures. In the figures, the left-most digit(s) of a reference number
25 identifies the figure in which the reference number first appears. The same numbers
are used throughout the drawings to reference like features and components.
3
[005] Figure 1 shows a network environment implementing a system for
managing charging of electric vehicles, in accordance with an embodiment of the
present subject matter.
[006] Figure 2 illustrates a battery management system for an electric vehicle,
5 according to an implementation of the present subject matter.
[007] Figure 3 shows a charging management terminal for managing charging
of electric vehicles, according to an embodiment of the present subject matter.
[008] Figure 4 illustrates a method for managing charging of electric vehicles,
in accordance with an implementation of the present subject matter.
10 [009] Figure 5 depicts a method of determining driver categorization for
drivers of electric vehicles, in accordance with an implementation of the present subject
matter.
DETAILED DESCRIPTION
15 [0010] Electric vehicles are generally easy to maintain, their electric motors
react quickly, and have very good torque. These and other advantageous features
relating to battery operated vehicles have led to electric vehicles, such as electric
rickshaws, hereinafter referred to as e-rickshaws, becoming a popular means of
transport. Electric vehicles use electricity stored in a battery to operate an electric
20 motor that in turn drives the wheels of the EVs. When depleted, the battery is recharged
using grid electricity, either from a wall socket or a charging unit.
[0011] In case of electric vehicles, such as e-rickshaws that are used for
commercial purposes, dedicated charging stations are provided for charging of the erickshaws, for example, on payment of fees in proportion to consumption of the
25 electricity or duration of charging.
[0012] Generally, the storage capability of an on-board battery used in the
electric vehicle is limited owing to limitations, such as space and weight constrains
dictated by design of the electric vehicle. For example, in case of e-rickshaws, space
4
for the battery may be constrained to allow more space for passengers. Consequently,
the electric vehicles need to be recharged frequently, for instance, on a daily basis, if
not more frequently. The need to charge the electric vehicles on a recurrent basis often
causes congestion at the charging stations.
5 [0013] The congestion at the charging stations is accentuated by the fact that
charging stations for electric vehicles are limited in number. Further limitations, such
as lack of availability of fast charging capabilities at many of the charging stations, for
example, due to cost reasons add to the congestion at the charging stations.
[0014] The congestion at the charging stations is also attributable to
10 simultaneous mutual requirement of many of the drivers driving electric vehicles in a
given area. Further, the congestion at the charging stations for e-rickshaws may be
significantly high during certain time periods during daytime. For instance, most of the
e-rickshaw drivers may operate the EVs during morning and evening time when high
number of passenger commuting, for instance, to offices, may avail the services of the
15 e-rickshaws and may opt to charge the e-rickshaws during noon time, for example,
when the e-rickshaw drivers may take a break, say, for lunch. The congestion at the
charging stations for e-rickshaws during such time periods often results in long waiting
period for the e-rickshaw drivers. This results not only in inconvenience to the erickshaw drivers but also leads to loss of business.
20 [0015] In some situations, it is also possible that certain charging stations for
e-rickshaws may face congestion while some other charging stations may remain
underutilized. For instance, due to lack of information of congestion at charging
stations in vicinity, an e-rickshaw driver may go to a congested charging station where
he may need to wait for his turn to charge his e-rickshaw while another charging station
25 in the vicinity may be available to allow charging of the e-rickshaw without any wait
time or significantly less wait time. Such fluctuating load demands and overburden of
load on a certain charging station of electric vehicles can have negative effects on their
performance. For example, overloading of some nodes of the charging stations can lead
5
to an increase in network losses and a degradation in voltage profiles at those nodes,
causing further unwanted congestion at the charging stations.
[0016] Thus, load of EVs to be charged needs to be managed such that the
congestion at the charging stations is reduced.
5 [0017] The present invention provides techniques for managing charging of
EVs, such as e-rickshaws to manage congestion at charging stations. The present
disclosure describes a system and method for managing charging of EVs by allocating
time slots for charging to each of the EVs at a given charging station thereby
distributing the load of EVs to be charged across the charging stations and across time
10 so as to eliminate congestion.
[0018] In an example embodiment, a time slot during which an EV may be
charged at a given charging station may be allocated based on a driver categorization
that may be determined for a driver of the EV. The driver categorization may be
indicative of driving behavior of the driver. In an example, driver categorization ‘A’
15 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 ‘5’ may exist wherein each driver categorization
is indicative of a ranking provided to the driver of the EV based on the driving behavior
of the driver.
20 [0019] In an example embodiment, for determining the driver categorization
for a driver of an EV, the driving behavior may be monitored over a predefined period
of time. In an example, the driving behavior may be based on the usage of a battery of
the EV by the driver. For instance, when a driver drives the EV at very high speed, a
rate of battery drainage is high. The output of the battery may be monitored to
25 determine instances of over speeding. More than a predefined number of instances of
over speeding over a predefined period of time may be indicative 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 battery usage to determine
6
the driving behavior. Accordingly, a variety of parameters may be monitored over a
period of time and may be used to determine the driving behavior of a driver. Based on
the determined driving behavior, the driver is assigned a driver categorization. Thus,
drivers with similar driving behavior may be assigned the same driver categorization.
5 [0020] In an example embodiment, the time slot during which an EV may be
charged at a given charging station may be allocated based on a driver categorization
such that drivers with driving behavior better than others, are assigned a more
comfortable or preferable time slot for charging their respective EVs. For instance, a
driver of an e-rickshaw having a driver categorization indicative of a good driving
10 behavior may be assigned a more preferable time slot for charging his e-rickshaw, for
example, during a time of the day when less commuters avail e-rickshaw services and
chances of the driver missing out on opportunities to service commuters is low. In
contrast, a driver of an e-rickshaw having a driver categorization indicative of a poor
driving behavior may be assigned a less preferable time slot, for example, during a time
15 of the day when more commuters may avail e-rickshaw services. The driver with poor
driving behavior may also be assigned an inconvenient time slot, for example, a time
slot during night time as opposed to a time slot during day time.
[0021] In an example embodiment, it is also possible to offer discounted rate
of electricity for charging the EV to the drivers having driver categorization indicative
20 of a good driving behavior. In an example, other services, such as servicing of the
battery may be offered for free or discounted rate to the drivers having driver
categorization indicative of a good driving behavior.
[0022] In an example, for allocation of a time slot for charging of an EV erickshaw at a given charging station, a current location of the EV is also taken into
25 account. This avoids a situation where a EV may be assigned a charging station located
very far away. In another example, for allocation of the time slot for charging, an
amount of current charge in a battery of the EV is also determined. Allocation of the
time slot in accordance with the remaining charge ensures that the battery is recharged
7
before the battery is completely depleted. In yet another example, current congestion
at each of the charging stations is also taken into consideration while assigning the time
slots for charging to the EVs. In an example, factors, such as location of the charging
stations, current availability of charging ports at the charging stations and charging
5 capabilities of each of the charging ports is also taken into account to assign time slots
in order to achieve most effective utilization of the charging stations.
[0023] A variety of parameters, such as the ones described above may be used
independently or in any combination with the driver categorization to compute a time
slot that results in most effective utilization of the charging stations. It is possible that
10 each of the parameters may be assigned a weightage. In an example, driver
categorization may also be assigned a weightage for determination of the time slot. To
illustrate with an example, a charging port having a fast charging capability may not
be assigned to a driver, despite him having driver categorization indicative of a good
driving behavior, if the EV does not support the fast charging capability and may
15 instead be assigned to another driver, irrespective of his driver categorization, in the
interest of most effective utilization of the charging stations.
[0024] The present system and method for managing charging of e-rickshaws
thus distribute the load of the e-rickshaws to be charged, across the charging stations
and across time so that not only the congestion is reduced, but the charging stations are
20 also used efficiently.
[0025] 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 electric
25 vehicles as applicable.
[0026] 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
8
illustrate the principles of the present subject matter along with examples described
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,
5 all statements herein reciting principles, aspects, and examples thereof, are intended to
encompass equivalents thereof. Further, for the sake of simplicity, and without
limitation, the same numbers are used throughout the drawings to reference like
features and components.
[0027] Figure 1 shows a network environment implementing a system 102 for
10 managing charging of electric vehicles, in accordance with an embodiment of the
present subject matter.
[0028] In an embodiment, the system 102 comprises a plurality of electric
vehicles 104-1, 104-2, ….., 104-n. (The figure depicts the EV 104-1 and EV 104-2
alone for the ease of depiction.) In an example, the electric vehicles 104-1, 104-
15 2…..104-n may be electric rickshaws, electric motorbikes or any other electric vehicles
that may need to charge by connecting to a charging station (not shown in figure).
[0029] Each of the EVs 104-1, 104-2…..104-n include at least one battery 106-
1, 106-2…..106-n, respectively. In an example, the batteries 106-1, 106-2…..106-n,
may be lithium ion batteries. Other examples of the batteries 106-1, 106-2…..106-n
20 include, nickel metal hydride batteries, sodium or zebra batteries.
[0030] Due to their utility and advantages over other types of batteries, lithium
ion batteries, which presently dominate the most recent group of electric vehicles in
development including consumer electronics, are preferred. A typical lithium ion
battery cell yields 80-90% of discharge efficiency. Examples of the types of lithium
25 ion batteries that can be incorporated in the electric vehicles 104-1, 104-2…..104-n can
be NCA, NMC, LMO, LifePO4.
[0031] Following description, to explain concepts relating to management of
charging of the batteries 106-1, 106-2…..106-n of the electric vehicles 104-1, 104-
9
2…..104-n, is provided in reference to EV 104-1 and the battery 106-1 of EV 104-1
for ease of explanation and is applicable to the other EVs 104-2, 104-3…..104-n and
their respective batteries 106-1, 106-2…..106-n.
[0032] The EV 104-1 includes a charging connector 108-1. The charging
5 connector 108-1 may be understood to be an input terminal to the battery 106-1 that
facilitates charging of the battery 106-1 at a charging station, by connecting itself to an
output terminal of a charging port at the charging station. Examples of the charging
connector 108-1 include but are not limited to mode 2, mode 3 charger or a plug type
1, or type 2.
10 [0033] In accordance with an example embodiment of the present subject
matter, the charging connector 108-1 functions in response to instructions given by a
battery management system 110-1. The battery management system 110-1 of the EV
104-1 is a component that acts as the control terminal of the battery 106-1. Among
other functions, battery management system 110-1 manages battery functions, such as
15 monitoring current battery charge level, ensuring low consumption of the battery when
in inactive mode, prevention from overcharging and under discharge. For the purpose
of managing the battery functions, the battery management system 110-1 measures
various parameters of the battery 106-1, such as battery cell voltage, temperature, etc.
In an example, the battery management system 110-1 may also measure various other
20 parameters of the EV 104-1, for example, speed or location of the EV 104-1.
Accordingly, the battery management system 110-1 may be communicatively coupled
to one or more sensors installed in the EV 104-1.
[0034] In an example, the battery management system, 110-1 may
communicate various parameters of the battery 106-1 to a management terminal 112.
25 Further the battery management system 110-1 may control the charging connector 108-
1 and in turn control the battery 106-1 based on control information received from the
management terminal 112. (Details of the battery management system 110-1 have been
discussed subsequently in reference to Figure 2.)
10
[0035] The management terminal 112 may be implemented as any of a variety
of conventional computing devices, including, server, a mainframe computer, a
desktop, a personal computer, a notebook or portable computer, a workstation, and a
laptop. Further, in one example, the system 102 may be a distributed or centralized
5 network system in which different computing devices may host one or more of the
hardware or software components of the system 102. The management terminal 112
can operate remotely or lie within the vicinity of the charging stations.
[0036] In one example of control of the EV 104-1 by the management terminal
112, the battery management system 110-1 may obtain speed of the EV 104-1, for
10 instance, from a sensor of the EV 104-1 and may communicate the same to the
management terminal 112. If the management terminal 112 determines that the speed
of the EV 104-1 needs to be reduced, for example, based on determining that a current
location of the EV 104-1 is a low speed zone, the management terminal 112 may direct
the battery management system 110-1 of the EV 104-1 accordingly. Based on the
15 instructions from the management terminal 112, the battery management system 110-
1 may reduce the battery output to the electric motor of the EV 104-1 to reduce speed
of the EV 104-1.
[0037] In another example of control of the EV 104-1 by the management
terminal 112, management terminal 112 may determine that the condition of the battery
20 106-1 of the EV 104-1 may have deteriorated based on monitoring maintenance and
usage of the battery 106-1 over a period of time. In such example situations, the
management terminal 112 may provide control signals to the battery management
system 110-1 of the EV 104-1 to control the charging connector 108-1 of the EV 104-
1 such that the charging connector 108-1 charges the battery 106-1 of the EV 104-1 at
25 a controlled rate of charging as opposed to a high rate of charging that may cause
damage to the battery 106-1 in its current deteriorated condition.
[0038] In an implementation of the system 102 for managing charging of
electric vehicles, the management terminal 112 may be implemented as a centralized
11
entity to control various EVs, such as electric vehicles 104-1, 104-2…..104-n
connected to the management terminal 112 in the network environment. The respective
battery management systems of the EV 104-1, 104-2…..104-n may use various
communication techniques to provide information relevant to charging conditions,
5 such as the battery level indication information, the data pertaining to the driver history,
the location of the EVs 104-1, 104-2…..104-n to the management terminal 112. The
management terminal 112 acts as a control node that contains logic circuitry for
processing of the data received from the battery management systems of plurality of
electric vehicles 104-1, 104-2…..104-n. The management terminal 112 may process
10 the received information along with other information such as information relating to
congestion at charging stations and location of charging stations to manage load on the
charging stations.
[0039] The electric vehicles 104-1, 104-2…..104-n may connect to the
management terminal 112 over a network 114. The network 114 may be a single
15 network or a combination of multiple networks and may use a variety of different
communication protocols. The network 114 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
20 Service (PCS) network, Time Division Multiple Access (TDMA) network, Code
Division Multiple Access (CDMA) network, Next Generation Network (NON), Public
Switched Telephone Network (PSTN). Depending on the technology, the
communication network 114 includes various network entities, such as gateways,
routers; however, such details have been omitted for the sake of brevity of the present
25 description.
[0040] In accordance with an example embodiment of the present subject
matter, user devices, such as those in possession of the drivers of the EVs may also be
communicatively coupled to the management terminal 112 over the network 114.
12
Example of user devices include, smartphones, personal digital assistant (PDAs), and
tablets or any other display device, consisting of applications that may interact with the
management terminal 112 to update information processed and transmitted to these
devices by the management terminal 112.
5 [0041] The management terminal 112 may associate user devices, such as user
devices 116-1 and 116-2 with their corresponding driver and EVs, for example, based
on a registration process. The management terminal 112 may provide information to a
driver of an EV by pushing such information to a user device associated with the driver.
For instance, the management terminal 112 may provide current information regarding
10 congestion level at various charging stations in vicinity of an EV, by flashing a message
on a display screen of the driver’s user device. In another example, the management
terminal 112 may provide warning message to a driver who may be over speeding or a
feedback/rating to a driver based on his driving behavior.
[0042] Reference is now made to Figure 2 that illustrates a battery management
15 system 200 for an electric vehicle, according to an implementation of the present
subject matter. As will be understood the battery management system 200 is similar to
the above-explained battery management system 110-1.
[0043] The battery management system 200 of an electric vehicle battery may
be understood a control system for a battery (not shown) of the EV, which monitors
20 and controls the battery status and operation. In an example implementation, the battery
management system 200 of the present invention, comprises a communication engine
202. The communication engine 202 performs communication between the battery
management system and the management terminal 112. The communication is
typically based on communication protocols. The communication engine 202 may use
25 several methods of serial or parallel communication, for instance and not limited to,
CAN bus communication, which is commonly used in automotive environments, DCBUS for serial communication, and different types of wireless communication. The
communication protocols can vary as per the hardware implementation.
13
[0044] The communication engine 202 communicates internally with various
sensors (not shown) that may be installed on the EV and transmits the inputs obtained
from the sensors to the management terminal 112. Based on the inputs obtained from
the sensors and other battery information communicated by the communication engine
5 202 to the management terminal 112, the management terminal 112 provides control
information to a control engine 204 of the battery management system 200 to take
actions to control the battery and in turn the operation of the EV.
[0045] The control engine 204 is responsible for controlling the trigger signals
to the charging connector. In an example implementation, the control engine 204
10 controls the charging of the battery as per predefined rule. The control engine 204
instructs a charging connector (not shown) of the battery to either connect to the supply
terminals of the charging station or stop the charging process. The control engine 204
also controls the charging schedule for the vehicle by ensuring the charging is done at
time slot allotted to the EV by the management terminal 112. The control engine 204
15 also ensures that the charging of the battery is in accordance with instructions provided
by the management terminal 112, if any. For example, if the management terminal 112
determines a rate of charging for the battery, the control engine 204 ensures that the
battery charges at the specified rate by controlling the charging connecter accordingly.
[0046] In the present description, the engine(s) may be implemented as a
20 combination of hardware and programming (for example, programmable instructions)
to implement certain functionalities of the engine(s), such as transmitting signals. In
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.
25 [0047] In an example implementation, the battery management system 200 of
the present invention, comprises a data store 206. The data store 206 may understood
as a memory component to store various data collated, manipulated or otherwise used
by the battery management system 200 in its operation. The memory component may
14
include any computer-readable medium including, for example, volatile memory (e.g.,
RAM), and/or non-volatile memory (e.g., EPROM, flash memory, etc.).
[0048] The data store 206 may store information, for example and not limited
to, inputs obtained from the sensors installed on the EV, such as EV position
5 information or current charge level information. The data store 206 may also store
instructions communicated to the battery management system 200 by the management
terminal 112, such as charging station congestion information. 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
10 information, information regarding driving actions. The driver’s history information
may include, among other things, information regarding any traffic accidents that the
driver may have been involved in.
[0049] Figure 3 shows a management terminal 300 for managing charging of
electric vehicles, according to an embodiment of the present subject matter.
15 [0050] The management terminal 300, 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, and/or any devices that manipulate signals based on operational
20 instructions. Among other capabilities, the processor(s) 302 is configured to fetch and
execute computer-readable instructions stored in a memory 304 of the computing
device 100. The system memory 304 may include any computer-readable medium
including, for example, volatile memory (e.g., RAM), and/or non-volatile memory
(e.g., EPROM, flash memory, etc.).
25 [0051] 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
15
single shared processor, or by a plurality of individual processors, some of which may
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
5 processor, application specific integrated circuit (ASIC), field programmable gate
array (FPGA), read only memory (ROM) for storing software, random access memory
(RAM), non-volatile storage. Other hardware, conventional and/or custom, may also
be included.
[0052] The interface(s) 306 may include a variety of software and hardware
10 interfaces that allow the management terminal 300 interact with battery management
systems of one or more EVs. Modules 308 and data 310 may reside in the memory 304.
The modules 308 include routines, programs, objects, components, data structures, and
the like, which perform particular tasks or implement particular abstract data types.
The modules 308 may also comprise other modules 312 that supplement functions of
15 the management terminal 300. The data 310 serves, amongst other things, as a
repository for storing data that may be fetched, processed, received, or generated by
the modules 308. The data 310 comprises other data 314 corresponding to the other
modules 312.
[0053] In operation, an EV communication module 316 of the management
20 terminal 300 allows the management terminal 300 to communicate with battery
management systems of one or more EVs. The EV communication module 316 enables
the management terminal 300 to receive information, such as sensor inputs and battery
information from the battery management systems. The EV communication module
316 may store the information received from the battery management systems as EV
25 input data 318 in the data 310 of the management terminal 300. Examples of
information received from the battery management systems of the EVs include current
battery level information, battery health information and location of the respective
EVs.
16
[0054] Based on the information received from the battery management
systems of the EVs and other data, such as driver categorization, driver’s history
information, congestion at charging stations and traffic congestion, that the
management terminal 300 may compute itself or obtain from other sources, a EV
5 control module 320 may generate control information for each of the EVs.
[0055] In an example implementation, the EV control module 320 may receive
the driver categorization of a given EV from the EV communication module 316. For
example, the EV communication module 316 may retrieve a previously stored driver
categorization of the EV from the EV input data 318 and provide the same to the EV
10 control module 320 for computation of the control data. The EV communication
module 316 may also fetch the driver categorization from an external source, such as
an external database configured to store driver categorization information pertaining to
the one or more EVs managed by the management terminal 300.
[0056] In another example implementation, the EV control module 320 may
15 compute the driver categorization for a given EV based on various information
corresponding to that EV received from the EV communication module 316. As will
be apparent based on the foregoing explanation, the EV control module 320 may
receive, among other things, information regarding usage of the battery of the EV and
data indicative of driving actions of the driver of the EV from the EV communication
20 module 316 to determine the driver categorization for the EV. The data indicative of
driving actions of the driver may be obtained from one or more sensors installed on the
EV. As discussed above, the EV communication module 316 may be configured to
receive the sensor inputs and battery information from the battery management system
of the EV.
25 [0057] In an example implementation, the EV control module 320 may also
factor in driver’s history information and/or maintenance history of the EV to compute
the driver categorization. The driver’s history information may include, among other
things, information regarding any traffic accidents that the driver may have been
17
involved in. The maintenance history of the EV may comprise information relating to
servicing and repair of the EV, current health and estimated remaining life of the
battery of the EV. For example, the current health of the battery may be based on a
discharge time taken by the battery to deplete charge to a predefined threshold upon
5 being completely charged. Accordingly, in one example, the EV communication
module 316 may retrieve the maintenance history of the EV from a customer database
that may maintain information relating to servicing of the EV. The customer database
may be internal or external to the management terminal 300 and may be maintained,
for example, by service providers who may provide maintenance related services, such
10 as routine servicing and repair to the EV. The maintenance history of the EV retrieved
by the EV communication module 316 may be used by the EV control module 320 to
compute the driver categorization.
[0058] In an example implementation, the EV control module 320 may also
consider customer feedback regarding the driver of the EV to compute the driver
15 categorization. In an example, the customer feedback may be a rating provided to the
driver of the EV by a customer. For instance, the rating may be on a predefined scale
of 1 to ‘n’ with each rating being based on a variety of predefined parameters, such as
customer’s assessment of the condition of the EV and driving skill of the driver. In
one example, the EV communication module 316 may enable a customer to provide a
20 rating to the driver of the EV. For the purpose, the EV communication module 316
may implement a communication interface to allow the customer to communicate with
the management terminal 300, for example, over the network 114 through a user
device. Based on the customer feedback and other above-mentioned information
received from the EV communication module 316, the EV control module 320 may
25 compute the driver categorization for generation of the control data.
[0059] In an example, the control information includes a time slots for charging
of each of the EVs at particular charging stations. The control information can also
include rate of charging for the batteries of each of the EVs. The EV control module
18
320 may store the control information generated for each of the EVs as EV control data
322 in the data 310 of the management terminal 300. The control information generated
for each of the EVs may be communicated to the battery management systems of the
respective EVs to enable control of the EVs based on the control information generated
5 the management terminal 300. Thus, the management terminal 300 controls the EVs to
manage load on the charging stations by distributing the load on the charging stations
by allocating different time slots for charging to the EVs.
[0060] Figure 4 illustrates a method 400 for managing charging of electric
vehicles, in accordance with an implementation of the present subject matter. Although
10 the method 400 may be implemented in a variety of electric vehicles, for the ease of
explanation, the present description of the example method 400 of managing charging
of electric vehicles is provided in reference to e-rickshaws. Also, although the method
400 may be implemented in a variety of computing devices, but for the ease of
explanation, the present description of the example method 400 of managing charging
15 of electric vehicles is provided in reference to the above-described management
terminal 112 or 300.
[0061] The order in which the method 400 is 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 method 400, or an alternative method.
20 Furthermore, the method 400 may be implemented by processor(s) or computing
device(s) through any suitable hardware, non-transitory machine readable instructions,
or combination thereof.
[0062] It may be understood that blocks of the method 400 may be performed
by programmed computing devices. The blocks of the method 400 may be executed
25 based on instructions stored in a non-transitory computer-readable 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.
19
[0063] Referring to Figure 4, at block 402, a driver categorization is determined
for a driver. The driver categorization may be indicative of driving behavior of the
driver. In an example, a first driver categorization may indicate a driving behavior that
is better than a second driver categorization. In another example, driver categorization
5 may rank drivers with a ranking of 1 through 10 based on a comparative analysis of the
driving behavior of the drivers. In an example, the driving behavior may be based on
usage of a battery of the EV by the driver.
[0064] The method of determining driver categorization is elaborated in
reference to Figure 5. As will be understood based on foregoing description, the
10 determination of driver categorization is done by monitoring EVs over a predefined
period. A driver categorization thus determined previously may be retrieved at block
402 by the management terminal.
[0065] At block 404, a present location of the electric vehicle is determined. In
an example, the current location may be located by the management terminal. The
15 management terminal may communicate with battery management system which may
provide the location information to the management terminal using a GPS of the EV.
The management terminal may also communicate with a user device associated with
the EV to determine the current location.
[0066] At block 406, information regarding remaining charge in the battery of
20 the electric vehicle is obtained. The level of battery remaining determines the charging
needs pertaining to the EV. In an example, the battery level determines the urgency for
charging required by an EV. The control engine of the battery management system
monitors the battery level information of the electric vehicle and may transmit the
information to the management terminal.
25 [0067] At block 408, current congestion at each of the charging stations is
determined. In an example, this information is obtained by the management terminal
by monitoring the charging stations. Information such as availability of charging port
and information gathered by count or proximity sensors installed at the charging
20
stations may also be communicated to the management terminal for determination of
the current congestion at respective charging stations. The congestion information
enables identification of charging stations that handle more load.
[0068] At block 410, based on the information determined at blocks 402
5 through 408, a time slot is allocated to the electric vehicle for charging at a charging
station. The time slot is based on utilization factor of each of the charging stations as
well as cost incurred on a EV to reach the charging station. Thus, wait time at a busy
charging station in proximity of the EV is weighted against cost that may be incurred
in travelling to a relatively free charging station that may be far away.
10 [0069] In an example, the information determined at blocks 402 through 408
may be used independently or in any combination with the driver categorization to
compute a time slots that results in most effective utilization of the charging stations.
It is possible that each of the parameters may be assigned a weightage. In an example,
driver categorization may also be assigned a weightage for determination of the time
15 slot. To illustrate with an example, a charging port having a fast charging capability
may not be assigned to a driver, despite him having driver categorization indicative of
a good driving behavior, if the EV does not support the fast charging capability and
may instead be assigned to another driver, irrespective of his driver categorization, in
the interest of most effective utilization of the charging stations.
20 [0070] At block 412, the time slot allocated to the electric vehicle for charging
at a charging station, as determined at block 408, is communicated to a driver of the
EV. Accordingly, a notification of the time slot and a location of the charging station
is provided to a user device of the driver of the EV.
[0071] In an example to ensure that the time slot allocated to the electric vehicle
25 for charging at a charging station is adhered to, the management terminal may also
convey the time slot and location of the charging station to the battery management
system of the EV. The battery management system of the EV may thus enable charging
21
of the battery only at said time slot and when engaged to a charging port at said
charging station.
[0072] Thus, the requirement that the congestion peak during off peak hours,
i.e., the duration of the day when the probability of the customer taking a ride is quite
5 low, should be regulated for effective utilization of the charging stations, such that a
charging station is not overcrowded is addressed by method 400. Further, the method
400 also ensures that in case of an emergency requirement of refueling for a specific
electric vehicle, the electric vehicle is directed to the first nearest or second nearest
charging station, as per availability of slot. Also, to prevent such sudden load demand
10 burden on the charging stations, the method 400 also ensures that the battery level of
each, as far as possible, electric vehicle be monitored, such that the vehicles have
individual time slots allotted to them for charging themselves beforehand.
[0073] The method 400, as explained previously, distributes the load on the
charging stations by allocating different time slots for charging to different EVs. The
15 allocation of the time slots, in one example implementation, is based on driving
categorization of drivers of the EVs.
[0074] Reference is now made to Figure 5 that depicts a method of determining
driver categorization for drivers of electric vehicles, in accordance with an
implementation of the present subject matter. Although the method 500 may be
20 implemented in a variety of electric vehicles, for the ease of explanation, the present
description of the example method 500 of determining driver categorization for drivers
of electric vehicles is provided in reference to e-rickshaws. Also, although the method
500 may be implemented in a variety of computing devices, for the ease of explanation,
the present description of the example method 500 for determining driver
25 categorization for drivers of electric vehicles is provided in reference to the abovedescribed management terminal 112 or 300.
[0075] The order in which the method 500 is described is not intended to be
construed as a limitation, and any number of the described method blocks may be
22
combined in any order to implement the method 500, or an alternative method.
Furthermore, the method 500 may be implemented by processor(s) or computing
device(s) through any suitable hardware, non-transitory machine-readable instructions,
or combination thereof.
5 [0076] It may be understood that blocks of the method 500 may be performed
by programmed computing devices. The blocks of the method 500 may be executed
based on instructions stored in a non-transitory computer-readable 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
10 magnetic tapes, hard drives, or optically readable digital data storage media.
[0077] Referring to Figure 5, at block 502, information regarding usage of a
battery of an EV is obtained. The information is obtained over a predefined period of
time. For the purpose, the battery may be monitored by the management terminal via
the battery management system of the EV on an ongoing basis or periodically. In an
15 example implementation, the control engine of the battery management system may
monitor the battery usage pattern and communicate the same to the management
terminal.
[0078] As mentioned previously, in an example, for determining the driver
categorization for a driver of the EV, the usage of the battery by the driver may be
20 monitored. For instance, when a driver drives the EV at very high speed, a rate of
battery drainage is high. Instances of prolonged duration of high rate of battery
drainage may be determined by the management terminal to assess the usage pattern
of the battery. In an example, factors like, regular charging of the battery by the driver
without overcharging and undercharging of the battery may also be obtained by the
25 management terminal to assess the usage pattern of the battery.
[0079] At block 504, data is obtained from the sensors installed on the EV,
wherein the data is indicative of driving actions of the driver of the EV. In an example,
sensors like accelerators, engine speed sensor, voltage sensor, measure the current
23
driving conditions of the EV. Deviation of the current driving conditions of the EV
from predefined ideal driving conditions may be indicative of poor driving skills and
in turn poor driving behavior. In an example, potentiometers at the accelerators
determine an amount of power that is consumed from the battery for application of
5 brakes, for instance the application of brakes can be in response to sudden appearance
of objects before the EV or precarious driving of the driver. Accordingly, driving
actions like sudden application of brakes can be indication of driving actions of the
driver. Also, speed of the EV at low-speed and high-speed zones may be monitored. In
another example, erratic driving actions, such as lane changing without activating a
10 turn indicator may monitored by the sensors.
[0080] In an implementation of the present method, the battery management
system of the EV monitors the sensor values for obtaining data relating to driving
actions. The battery management terminal via the communication engine provides the
monitored sensor values to the management terminal for assessment of driving skills
15 and in turn driving behavior of the driver based on the driving actions of the driver.
[0081] At block 506, maintenance history of the EV is obtained. The
maintenance history of the EV includes, among other data, the history of maintenance
provided to battery of the EV. In an example, the lithium ion batteries may be employed
in the EV, and may require routine maintenance, such as servicing and repair. The
20 servicing may be, for example, routine check-up of charge status of the lithium ion
batteries, such that the batteries approaching the end of their estimated life are replaced.
In an example, it is taken into consideration that if the battery run time drops below
80% of the original time, and the battery charge time increases significantly, the
batteries must be replaced.
25 [0082] In an implementation of the present method, the management terminal
may obtain the maintenance history of the EV from a customer database that may be
an internal or external data store comprising maintenance records pertaining to EVs
that are serviced, for example, by a certain service provider. In an example, along with
24
the maintenance history of the EV, the management terminal may also obtain driver’s
history comprising information regarding any traffic accident relating to the driver.
[0083] At block 508, information regarding customer feedback regarding a
driver of the EV is obtained. The customer feedback may be obtained by the
5 management terminal through an application employed for providing ride services. In
an example, the customer feedback can be obtained by the customer providing rating
to the driver of the EV. Further, the feedback can also include remarks for the driver
based on driver’s driving skills. In an example, the customer feedback acts as a direct
channel for driver categorization as it is a real time analysis/experience submitted as
10 feedback by the customer to the management terminal.
[0084] At block 510, computation of driver categorization for the driver, based
on one or more of the obtained information is done. In an example, the driver
categorization may include customer feedback, driver’s history, usage of battery of the
EV by the driver, maintenance history, data obtained from sensors or combinations
15 thereof. The driver categorization is indicative of the driver’s driving skills, i.e., the
categories is based on a good driving behavior or a poor driving behavior of the driver
along with other parameters. In another example, driver categorization may rank
drivers with a ranking of 1 through 10 based on a comparative analysis of the driving
behavior of the drivers.
20 [0085] In an example, driver categorization can be based on a predefined
weightage assigned to one or more of the obtained information at block 502 through
508. To illustrate an example, the driver may be given a categorization of a poor driver
even if his user feedback is good, if his battery usage pattern is poor, in view of safe
driving considered in public interest.
25 [0086] Categorization of drivers into categories indicative of good or poor
driving behavior, also ensures promoting a desirable usage pattern of battery, which
further ensures increase in battery life of the battery and its effective utilization.
Determination of the driver categorization and making drivers aware of their respective
25
driver categorization provides for incentivization for the driver to attain better driver
categorization.
[0087] For instance, a driver of an e-rickshaw having a driver categorization
indicative of a good driving behavior may be assigned a more comfortable time slot
5 for charging his e-rickshaw, while a driver of an e-rickshaw having a driver
categorization indicative of a poor driving behavior may be assigned a less preferable
time slot, for example, an inconvenient time slot, such as a time slot during night time
as opposed to a time slot during day time. In another example, drivers having driver
categorization indicative of a good driving behavior may be offered discounted rate of
10 electricity for charging the EV. In an example, other services, such as servicing of the
battery may be offered for free or discounted rate to the drivers having driver
categorization indicative of a good driving behavior.
[0088] Thus, by allocation of different time slots to different drivers based on
their driver categorization as ascertained based on the method 500, the requirement of
15 regulation of congestion is addressed. Further, the method 500 also ensures that a
driver’s categorization indicative of poor driving behavior is identified, for example,
for corrective measures to be implemented. Furthermore, incentivization for the driver
to attain better driver categorization promotes safe driving as well as judicious usage
of battery.
20 [0089] Although the subject matter has been described in considerable detail
with reference to certain examples and implementations thereof, other implementations
are possible. As such, the present disclosure should not be considered limited to the
description of the preferred examples and implementations contained therein.

I/We Claim:

1. A method comprising:
obtaining information regarding usage of a battery of an electric vehicle;
obtaining, from one or more sensors installed on the electric vehicle, data
5 indicative of driving actions of a driver of the electric vehicle; and
determining a driver categorization for the driver of the electric vehicle based at
least in part on the information regarding usage of the battery and the data indicative
of the driving actions, wherein driver categorization for the driver is indicative of
driving behavior of the driver.
10
2. The method as claimed in claim 1 further comprising allocating a time slot for
charging at a charging station to the electric vehicle based on the driver categorization.
3. The method as claimed in claim 2 further comprising controlling a charging
15 schedule of the electric vehicle by enabling the charging to be done only at the time
slot allotted to the electric vehicle.
4. The method as claimed in claim 1 further comprising determining a rate of
charging for the battery to the electric vehicle based on the driver categorization.
20
5. The method as claimed in claim 1 further comprising providing a discounted
rate of electricity for charging the electric vehicle based on the driver categorization.
6. The method as claimed in claim 2, wherein allocating the time slot for charging
25 to the electric vehicle is further based on at least one of an amount of current charge
in the battery of the electric vehicle, congestion at the charging station, current
location of the electric vehicle and location of the charging station.
27
7. The method as claimed in claim 1 further comprising obtaining at least one of:
maintenance history of the electric vehicle; and
driver’s history comprising information regarding any traffic accident relating
to the driver, wherein
5 the driver categorization is based at least in part on the maintenance history and
the driver’s history.
8. The method as claimed in claim 1 further comprising obtaining information
10 regarding customer feedback regarding the driver of the electric vehicle, the driver
categorization being based at least in part on the information regarding customer
feedback.
9. A management terminal comprising:
15 a processor;
an EV communication module, coupled to the processor, to:
receive information regarding usage of respective batteries of a
plurality of electric vehicles from corresponding battery management systems
of the plurality of electric vehicles; and
20 EV control module, coupled to the processor, to:
obtain driver categorization corresponding to each of the plurality of
electric vehicles, wherein the driver categorization of each of the plurality of
electric vehicles corresponds to driving behavior of respective drivers of each
of the plurality of electric vehicles; and
25 generate control information for each of the plurality of electric
vehicles, the control information comprising a time slot for charging of each
of the plurality of electric vehicles at least one charging station.
28
10. The management terminal as claimed in claim 9, wherein the EV
communication module is to further provide the time slot allocated to each of the
plurality of electric vehicles and the location of the at least one charging station to a
user device of respective drivers of each of the plurality of electric vehicles.
5
11. The management terminal as claimed in claim 9, wherein the EV
communication module is to further receive data indicative of driving actions of the
driver of each of the plurality of electric vehicles, wherein the data is obtained from
one or more sensors installed on each of the plurality of electric vehicles, and wherein
10 the EV control module is to compute the driver categorization of each of the plurality
of electric vehicles is based on the driving actions of the respective drivers.
12. The management terminal as claimed in claim 9, wherein the control
information further comprises a rate of charging for the batteries of each of the
15 plurality of electric vehicles.
13. The management terminal as claimed in claim 9, wherein the EV
communication module is to further receive maintenance history of each of the
plurality of electric vehicles, and wherein the driver categorization of each of the
20 plurality of electric vehicles is based at least in part on maintenance history of
respective electric vehicles.
14. The management terminal as claimed in claim 9, wherein the EV
communication module is to further receive customer feedback regarding the drivers
25 of each of the plurality of electric vehicles, and wherein the driver categorization of
each of the plurality of electric vehicles is based at least in part on the customer
feedback regarding the respective drivers.
29
15. An electric vehicle comprising:
at least one battery;
a charging connector to facilitate charging of the at least one battery; and
a battery management system to control a charging schedule for the electric
5 vehicle by controlling the charging connector to charge the at least one battery at time
slots allotted to the electric vehicle.
16. The electric vehicle as claimed in claim 15, wherein the time slots are
communicated to the battery management system by a management terminal
10 implemented to control a plurality of electric vehicles.
17. The electric vehicle as claimed in claim 15, wherein the time slots allotted to the
electric vehicle is based on driver categorization of a driver of the electric vehicle,
wherein the driver categorization corresponds to driving behavior of the driver of the
15 electric vehicle.