FIELD OF THE INVENTION:
[0001] The present invention relates to field of automobiles. More particularly, the
present invention relates to a system and method for providing correct range or drivable
distance estimation in electric vehicles.
BACKGROUND OF THE INVENTION:
[0002] Automobile industry has shown tremendous advancement in last few decades.
The advancement has been in every niche of technology, be it making engines lighter and
faster, improvement in aerodynamics etc. One such area where automobile industry has
made tremendous improvement is switching from Internal combustion engines vehicles to
electric vehicles. Electric cars are very pleasant to drive compared to internal combustion
engine vehicles. The major difference being that they are extremely quiet and are therefore
very relaxing on the move. They also deliver power in an incredibly smooth manner, which
eliminates the need for a gearbox, making the driving experience even easier.
[0003] As petrol and diesel prices continue to rise and more stringent conditions come
into force on vehicle emissions, motor manufacturers are being encouraged to develop
alternatives to traditional internal combustion engine vehicles (ICEVs). The maintenance of
Electric vehicles (EVs) should be less than internal combustion engine vehicles, due to the
lack of a gearbox and the oils and cooling fluids that are associated in ICEVs. Electric motors
have far less moving parts than conventional petrol / diesel engine too. The running costs of
electric vehicles are considerably less for the average trip.
[0004] The beauty of electric vehicles is that most electric vehicles will be charged
overnight at home, as most journeys will be well within their range. However, these electric
vehicles have their own disadvantages such as range anxiety that arise due to change of some
real-time parameters such as rolling resistance that depends on the tire pressure.
[0005] Further advancing on this technology, systems for range estimation were
introduced to overcome the problem of range anxiety. In these systems pre-programmed
fixed values are used for the parameters required for range estimation such as drive-cycle
employed, tire rolling resistance and aero-dynamic losses. However, one of the parameter i.e.,
the tire rolling resistance play an important role in real time situation. Tire rolling resistance
gets significantly increased if tire pressure is below a recommended value. Tire pressure is
not a major concern for internal combustion engine vehicles but plays an important role in

electric vehicles. In electric vehicles, decrease in tire pressure would lead to early battery
depletion and may cause serious discomfort to an electric vehicle driver. For example,
decrease in tire pressure below a certain threshold may lead to stoppage of vehicle.
Although, prior art systems consider fixed value of tire pressure when performing range
estimation but still fails to provide accurate value of range estimation.
[0006] Thus, there exist a need for a system and a method that may be used to
estimate correct range or drivable distance for a battery operated vehicle. Based on such
estimation, the driver can plan his journey or decide to optimally fill-up the tire so as to avail
stipulated range for a given driving cycle.
SUMMARY OF THE INVENTION:
[0007] Before the present system and method is described, it is to be understood that
this disclosure is not limited to the particular systems, and methodologies described, as there
can be multiple possible embodiments of the present disclosure which are not expressly
illustrated in the present disclosure. It is also to be understood that the terminology used in
the description is for the purpose of describing the particular versions or embodiments only
and is not intended to limit the scope of the present disclosure.
[0008] In an aspect, the present disclosure describes a system for estimating drivable
distance for a battery-operated vehicle. The system comprises at least one sensing unit and a
drivable distance estimation unit. The at least one sensing unit comprising: a sensor for
sensing tire pressure value and a transmitter for transmitting the sensed tire pressure value.
The system also comprises a drivable distance estimation unit operatively coupled to the at
least one sensing unit, said drivable distance unit comprising: a memory configured for
storing a table, said table defining a mapping between a plurality of tire pressure values and a
plurality of rolling resistance coefficient values; a receiver for receiving the at least one
sensed tire pressure value; and a processor configured for: determining at least one rolling
resistance coefficient value from the table corresponding to the at least one sensed tire
pressure value; and estimating drivable distance based on the at least one determined rolling
resistance coefficient value.
[0009] In another aspect of the system, as disclosed, the drivable distance is estimated
in kilometers. The processor is configured for estimating drivable distance based on the at
least one determined rolling resistance coefficient value by: determining available battery

energy (Eavailable); determining battery energy consumption/kilometer (Econsumed); and
estimating drivable distance as a ratio of the available battery energy (Eavailable) and battery
energy consumption/kilometer (Econsumed).
[0010] In yet another aspect of the present disclosure, as disclosed, the processor is
configured for determining the battery energy consumption/kilometer (Econsumed) by:
determining power (Pacc) required to accelerate the battery-operated vehicle; determining
power (Proad-load) required to overcome aerodynamic drag force and rolling friction force; and
determining the battery energy consumption/kilometer (Econsumed) as the summation of (Pacc)
and (Proad-load); wherein (Pacc) is determined based on the following:
(Pacc)=M x a x v(t), where M is the mass of the battery-operated vehicle, a is the
acceleration of the vehicle and v(t) is the instantaneous velocity of the vehicle; and
wherein (Proad-load) is determined based on the following:
(Proad-load) = Ftraction x v(t), where Ftraction is summation of aerodynamic drag force
(Faerodynamic) and rolling friction force (Frolling), and v(t) is the instantaneous velocity of the
battery-operated vehicle.
[0011] In still another aspect of the present disclosure, as disclosed, wherein the
processor is configured for determining the aerodynamic force by:
Faerodynamic =1/2 ρ v2 Cd A,where ρ is air density, v is the speed of the vehicle, A
is frontal area and Cd is the coefficient of aerodynamic resistance.
[0012] In another aspect of the present disclosure, as disclosed, wherein the processor
is configured for determining the rolling friction force (Frolling) by:
Frolling = μr.W,
where, μr is the rolling resistance coefficient of the vehicle determined from the table based
on the sensed tire pressure and W is the weight of the battery-operated vehicle.
[0013] In yet another aspect of the present disclosure, as disclosed, wherein the
processing unit is configured for estimating drivable distance based on the at least one
determined rolling resistance coefficient value by: performing summation of the at least one
determined rolling resistance coefficient value to determine a resultant rolling resistance

coefficient value; and estimating drivable distance based on the determined resultant rolling
resistance coefficient value.
[0014] In still another aspect of the present disclosure, wherein a value of the rolling
resistance corresponds to a value of the sensed tire pressure or a value of the rolling
resistance corresponds to a range of sensed tire pressure values.
[0015] In another aspect, the present disclosure describes a method for estimating
drivable distance for a battery-operated vehicle. The method, as discloses comprising:
sensing at least one tire pressure value; determining at least one rolling resistance coefficient
value corresponding to the at least one sensed tire pressure value from a table storing a
mapping between a plurality of tire pressure values and a plurality of rolling resistance
coefficient values; and estimating drivable distance based on the at least one determined
rolling resistance coefficient value.
[0016] In yet another aspect of the present disclosure, as disclosed, the drivable
distance is estimated in kilometers and wherein estimating drivable distance based on the at
least one determined rolling resistance coefficient value comprises: determining available
battery energy (Eavailable); determining battery energy consumption/kilometer (Econsumed); and
estimating drivable distance as a ratio of the available battery energy (Eavailable) and battery
energy consumption/kilometer (Econsumed).
[0017] In still another aspect of the present disclosure, as disclosed, wherein
determining the battery energy consumption/kilometer (Econsumed) comprises: determining
power (Pacc) required to accelerate the battery-operated vehicle; determining power (Proad-load)
required to overcome aerodynamic drag force and rolling friction force; and determining the
battery energy consumption/kilometer (Econsumed) as the summation of (Pacc) and (Proad-load);
wherein (Pacc) is determined based on the following:
(Pacc)=M x a x v(t), where M is the mass of the battery-operated vehicle, a is the
acceleration of the vehicle and v(t) is the instantaneous velocity; and
wherein (Proad-load) is determined based on the following:
(Proad-load) = Ftraction x v(t), where Ftraction is summation of aerodynamic drag force (Faerodynamic)
and rolling friction force (Frolling), and v(t) is the instantaneous velocity of the batteryoperated
vehicle.

[0018] In another aspect of the present disclosure, as disclosed, wherein determining
the aerodynamic drag force comprises: determining the aerodynamic drag force Faerodynamic
based on:
Faerodynamic =1/2 ρ V2 Cd A,
where ρ is air density, V is the speed of the vehicle, A is frontal area and Cd is the coefficient
of aerodynamic resistance.
[0019] In yet another aspect of the present disclosure, as disclosed, wherein
determining the rolling friction force (Frolling) comprises: determining the rolling friction force
(Frolling) based on:
Frolling = μr.W,
where, μr is the rolling resistance coefficient of the vehicle determined from the table based
on the sensed tire pressure and W is the weight of the battery-operated vehicle.
[0020] In still another aspect of the present disclosure, as disclosed, wherein
estimating drivable distance based on the at least one determined rolling resistance coefficient
value comprises: performing summation of the at least one determined rolling resistance
coefficient value to determine a resultant rolling resistance coefficient value; and estimating
drivable distance based on the determined resultant rolling resistance coefficient value.
[0021] In another aspect of the present disclosure, as disclosed, wherein a value of the
rolling resistance corresponds to a value of the sensed tire pressure or a value of the rolling
resistance corresponds to a range of sensed tire pressure values.
[0022] In the above paragraphs, the most important features of the invention have
been outlined, in order that the detailed description thereof that follows may be better
understood and in order that the present contribution to the art may be better understood and
in order that the present contribution to the art may be better appreciated. There are, of
course, additional features of the invention that will be described hereinafter and which will
form the subject of the claims appended hereto. Those skilled in the art will appreciate that
the conception upon which this disclosure is based may readily be utilized as a basis for the
designing of other structures for carrying out the several purposes of the invention. It is

important therefore that the claims be regarded as including such equivalent constructions as
do not depart from the spirit and scope of the invention.
BRIEF DESCRIPTION OF DRAWINGS:
[0023] Further aspects and advantages of the present invention will be readily
understood from the following detailed description with reference to the accompanying
drawings, where like reference numerals refer to identical or functionally similar elements
throughout the separate views. The figures together with the detailed description below, are
incorporated in and form part of the specification, and serve to further illustrate the aspects
and explain various principles and advantages, in accordance with the present invention
wherein:
[0024] Fig. 1 illustrates graphical representation of a typical driving cycle of an
electric vehicle.
[0025] Fig. 2 illustrates flowchart representation of a typical range estimation process
used in the prior art.
[0026] Fig.3 illustrates flowchart representation of estimation of drivable distance
process based on real-time monitoring of tire pressure, according to an embodiment of
present invention.
[0027] Fig. 4 explain the exemplary embodiment of system for estimating drivable
distance in battery-operated vehicles, by way of block diagram.
[0028] Skilled artisans will appreciate that elements in the drawings are illustrated for
simplicity and have not necessarily been drawn to scale. For example, the dimensions of
some of the elements in the drawings may be exaggerated relative to other elements to help to
improve understanding of aspects of the present invention.
DETAILED DESCRIPTION OF DRAWINGS:
[0029] The present invention will be described herein below with reference to the
accompanying drawings. In the following description, well known functions or constructions
are not described in detail since they would obscure the description with unnecessary detail.
[0030] In the present document, the word "exemplary" is used herein to mean "serving

as an example, instance, or illustration." Any embodiment or implementation of the
present subject matter described herein as "exemplary" is not necessarily to be construed
as preferred or advantageous over other embodiments.
[0031] While the disclosure is susceptible to various modifications and alternative
forms, specific embodiment thereof has been shown by way of example in the drawings
and will be described in detail below. It should be understood, however that it is not
intended to limit the disclosure to the particular forms disclosed, but on the contrary, the
disclosure is to cover all modifications, equivalents, and alternatives falling within the
scope of the disclosure.
[0032] The terms “comprises”, “comprising”, “include(s)”, or any other variations
thereof, are intended to cover a non-exclusive inclusion, such that a setup, arrangement,
unit, system or method that comprises a list of components or steps does not include
only those components or steps but may include other components or steps not expressly
listed or inherent to such setup or arrangement or unit or system or method. In other
words, one or more elements in a system or apparatus or unit or arrangement proceeded
by “comprises… a” does not, without more constraints, preclude the existence of other
elements or additional elements in the system or apparatus or unit or arrangement.
[0033] The present disclosure presents a system and method for estimating the
accurate drivable distance. In other words, the present invention provides an accurate range
estimation to driver of the electric vehicle. To achieve this, a real-time value of tire pressure
is sensed and based on the real-time pressure value, rolling resistance of tire is determined
from a calibration table. On the basis of rolling resistance computed from calibration table,
actual value of energy consumed per km is computed which helps in estimating the drivable
distance. The real-time estimation of tire pressure is used for correcting the range estimation
and for providing an early alert to the driver of electric vehicle. Based on that alert the driver
can choose to fill-up the tire with air more frequently or plan his journey. In this way, the
present invention provides cost effective and reliable range estimation for electric vehicles.
[0034] Figure 1 discloses a graphical representation of typical driving cycle of an
electric vehicle. The graph of driving cycle includes a series of data points representing the
speed of a vehicle versus time. The graph helps to determine the distance by calculating the

area under the data points. Instantaneous power consumed at every point of the driving cycle
P(t) may be estimated with the help of below components:
• Power needed to accelerate the vehicle mass (Pacc)
P(t) = Pacc(t) + Proad-load(t) --------------------1
Where, P(t) is the total power which is the resultant of summation of power used in
acceleration of the vehicle (Pacc) and the power utilized in overcoming traction forces. The
power needed to accelerate the vehicle mass (Pacc(t)) may be computed through Newton’s
second law of motion.
Pacc(t)= F*V(t) ---------------------2
F=M.a = M*dv/dt (Newton’s second law of motion)
Where, change in velocity is calculated between two points of a driving cycle and M is the
mass of the battery-operated vehicle and V(t) is the instantaneous velocity of the battery
operated vehicle.
• power consumed in over-coming the aero-dynamic drag force and rolling
resistance force of the tire (Proad-load)
Proad-load(t) = Ftraction . V(t) --------------------3
Where, Proad-load(t) is the power consumed in over-coming the aero-dynamic drag and rolling
resistance of the tire. The term Ftraction represents the tractive force needed for the vehicle to
overcome resistive force generated due to vehicle parameter and V(t) is the instantaneous
velocity of the vehicle as per a driving cycle.
Further, Ftraction can be computed based on following equation:
Ftraction = Rolling Resistance Force (Frolling)+ Aerodynamic Drag Force (Faerodynamic) ---------4
The term rolling resistance force (Frolling) depends on tire pressure. Aerodynamic drag force
(Faerodynamic) is computed from aerodynamic parameters of the vehicle and is proportional to
the square of the vehicle speed. At lower speeds rolling resistance dominates equation 4 and
at mid-speed Ftraction is comparable to aero-dynamic force.
Frolling = μr.W ---------------5

Where, μr is a constant, called the coefficient of rolling friction and W is the entire weight of
the rolling object.
Faerodynamic =1/2 ρ V2 Cd A -----------------6
Where, Faerodynamic is the aerodynamic drag force, ρ is the density of the fluid i.e air, V is the
speed of the vehicle, A is frontal area and Cd is the coefficient of aerodynamic resistance. The
value of Ftraction get significantly impacted by rolling resistance up to mid speed. Hence, in
city driving cycle, it is a determining factor for estimating the drivable distance.
P(t) can be integrated for the amount of time across the driving cycle for which the
cumulative area under the curve is 1 Km . This gives us energy consumed per Km.
Total energy consumed over a driving cycle for 1 Km = E(Total) = ∫P(t)dt --------------7
The drivable distance or range can be estimated by dividing total energy available in the
battery by energy consumed per Km.
[0035] The major vehicle resistance force on level ground is the rolling resistance of
the tires. At low speeds on hard pavement, the rolling resistance is the primary motion
resistance force. In fact, the aerodynamic resistance becomes equal to the rolling resistance
e.g at speeds of 80-100 km/h. For off-highway, level ground operation; the rolling resistance
is only significant retardation force. While other resistance act only under certain conditions
of motion, rolling resistance is present from the instant the wheels begin to turn. Further,
rolling resistance has another undesirable property, a large part of power expended in a
rolling wheel is converted in to heat within the tire. Hence, the rolling resistance is a limiting
factor in tire performance and estimation of drivable distance.
[0036] Figure 2 discloses a typical range estimation process used in the prior art. In
the step 201, the power consumed is calculated for vehicle acceleration during per km of a
driving cycle. In next step 202, the actual value of energy consumed per km of the driving
cycle is calculated on the basis of rolling resistance, aero-dynamic drag and vehicle
acceleration. In this technique, a fixed value of rolling resistance and other parameters is used
for calculating the energy consumption per km. In step 203, range is estimated based on the
available batter power and the energy consumed per km. As the range is estimated based on
fixed parameters which is always high than the range estimated on the basis of real-time
parameters. Therefore, the problem of the prior art leads to over-estimation of the range as

the actual factors which severely impact the range are not taken in to account. Further, fixed
value of tire pressure or rolling resistance provide a false indication about the drivable range
to the driver which can impact his journey.
[0037] Figure 3 discloses an improved method for estimating the drivable distance
according to one of the embodiments of present invention. The drivable distance is the
distance which can be easily passed with the currently available battery charge. The present
invention provides an accurate estimation about how much distance can be achieved with the
currently available battery. Present invention provides necessary correction based on the
actual (real-time) reading of tire pressure where the tire pressure is read from the sensing unit.
In prior art a fixed value of tire pressure is considered which provides an over estimation of
drivable distance range than actually available range. To achieve the accurate drivable
distance, in present invention, in one of the embodiment, tire pressure of one of the tire of
battery-operated vehicle is taken. Pressure sensor is used to sense the pressure from one of
the tire of battery-operated vehicle. Based on the sensed tire pressure, a value of
corresponding rolling resistance coefficient is determined from a calibration table. The
calibration table is used to store the values of rolling resistance coefficients and tire pressures.
In an exemplary embodiment, the rolling resistance coefficient can be a single value for
multiple tire pressures. In other words, there can be a single rolling resistance for a range of
tire pressures that can be used in the above mentioned equation 5 for calculating the force
required to overcome the rolling resistance. In another embodiment, the tire pressure is
sensed by the sensing unit from all the tires of the battery operated vehicle and a
corresponding value of rolling resistance coefficient is determined for all the sensed or
measured tire pressures. Afterwards, all the values of rolling resistance coefficients which is
determined corresponding to sensed pressure(s) are added up to generate a final determined
value of rolling resistance.
[0038] In step 301, the power is computed based on the vehicle acceleration during
per km of driving cycle. In step 302, corresponding to above defined embodiments, actual
value of rolling resistance is determined from a calibration table of tire pressure vs. rolling
resistance. For example, if the battery-operated vehicle is a car, then in one of the
embodiment, the tire pressure is sensed from one of its tire and a corresponding value of
rolling resistance coefficient can be taken for measuring the Proad-load which is finally used in
next step. In another embodiment, if the tire pressure is sensed from all the four tires then a
corresponding value of rolling resistance coefficient is determined from the calibration table

for all the four sensed pressures. Afterwards, all the rolling resistance coefficients obtained
corresponding to different sensed pressures of all the tires are added up to get a final value of
rolling resistance coefficient. Similar type of computation can be performed in a two-wheeler
or a three-wheeler battery-operated vehicle. In step 303, actual value of energy consumed per
km is computed on the basis of rolling resistance computed in step 302. The other parameters
such as aero-dynamic drag force and vehicle acceleration are considered in same way as
considered in prior art. In another embodiment, the value of the parameters used in aerodynamic
drag is also calculated or measured in real-time from different sensing units. In step
304, the drivable distance is estimated on the basis of energy available in the battery divided
by the energy consumed per km of the driving cycle as calculated in step 303.
􀜦􀝎􀝅􀝒􀜽􀜾􀝈􀝁 􀝀􀝅􀝏􀝐􀜽􀝊􀜿􀝁 􀝋􀝎 􀝎􀜽􀝊􀝃􀝁 (􀝅􀝊 􀜭􀝉) =
Available battery energy
􀜾􀜽􀝐􀝐􀝁􀝎􀝕 􀝁􀝊􀝁􀝎􀝃􀝕 􀜿􀝋􀝊􀝏􀝑􀝉􀝌􀝐􀝅􀝋􀝊/􀝇􀝅􀝈􀝋􀝉􀝁􀝐􀝁􀝎
--------------8
At a particular instant of time, the status of battery is monitored which is treated as available
battery energy. The other factor that is battery energy consummation/km is determined in step
303 based on the present value of tire pressure and other parameters as defined in equation 2
and 6. In this way, an accurate estimation of drivable distance may be provided to the driver
of electric vehicle.
[0039] Figure 4 discloses a system for providing accurate drivable distance value for
battery-operated vehicle according to an embodiment of the present invention. The system
400 represent a system that may comprise a sensing unit 401 and a drivable distance
estimation unit 402. The sensing unit 401 comprises one or more sensors 403 to sense the tire
pressure of the battery operated vehicle. The sensing unit also comprises a transmitter 404 to
transmit the pressure sensed by the one or more sensors 403 mounted on the tire of the
battery-operated vehicle. In an embodiment, one of the sensor 403 can be a pressure sensor or
any other sensor which is also capable of measuring pressure in the tire. For example, a
sensing unit 401 comprises a pressure sensor 403 mounted on the tire of the battery-operated
vehicle. The pressure sensor 403 is mounted on each of the tire of the battery operated
vehicle which can sense real-time value of the tire pressure. The transmitter 404 of the
sensing unit 401 may send the value of sensed tire pressure of each tire to the drivable
distance estimation unit 402. The drivable distance estimation unit 402 may comprise a
memory 405, a receiver 406, a processor 407, a battery monitoring module 408 etc. The
receiver 406 of the drivable distance estimation unit 402 will receive the value of the sensed

tire pressure transmitted from the transmitter 404. In an embodiment, the transmitter 404 is a
radio frequency transmitter and the receiver 406 is a radio frequency receiver. The signals
from the radio frequency transmitter 404 are transmitted to the radio receiver 406 via
communication link 411. The signals received by the radio frequency receiver 406 may be
computed by the processor 407 at the drivable distance estimation unit 402. The processor
407 is coupled to a memory 405 that stores a calibration table. The calibration table contains
different entries of the rolling resistance coefficients against different values of tire pressures.
A sample calibration table is provided below:
Table 1: Variation of tire pressure vs. coefficient of rolling resistance
Sr. No Tire pressure (psi) Rolling resistance Coefficient
(μr)
1 40 0.0132
2 25 0.0159
3 15 0.0214
In another embodiment, the table may contain either entries of coefficient of rolling
resistance for each value of tire pressure or there may be a single value of rolling resistance
coefficient available against a range of tire pressure. For example, for estimating the drivable
distance, the value of the rolling resistance coefficient is considered as 0.0132 for pressure
range 35-40 psi.
[0040] The value of rolling resistance coefficient is taken in to account for all the tires
of the battery operated vehicle and based on the rolling resistance coefficient the value of
rolling resistance force is calculated. Based on the value calculated for rolling resistance force
and the aero dynamic force, the total traction force is evaluated which is used for calculation
of Proad-load as mentioned in equation 3. The other power factor which is responsible for
acceleration of the vehicle (Pacc) is calculated from the above mentioned equation 2. The
processor 407 can be used for summing the power calculated from the equation 2 and
equation 3. Total power (Ptotal) calculated as a result of summation of the powers calculated in
equations 2 and 3 is integrated for the amount of time across the driving cycle for which the

cumulative area under the curve is 1Km . This gives us battery energy consumption/kilometer
(as defined in equation 7).
[0041] The battery operating module 408 of the system may be used to determine the
current state of battery charge i.e available battery energy in the battery-operated vehicle.
Based on the current charge state of the battery, the processor 407 may determine the drivable
distance of the battery operated vehicle. In particular, the value of the available battery
energy (Eavailable) and battery energy consumption/kilometer (Econsumed) will be used to provide
the estimation of drivable distance for the battery operated vehicle (as defined in equation 8).
The drivable distance estimated by the processor 407 is provided to the range display unit
410 which may provide an alert to the driver of electric vehicle regarding range or drivable
distance available in kms(as calculated by the method disclosed in figure 3). In another
embodiment, all the processing of different equations is taken in meters instead of Kms. The
battery charge monitoring module 408 may provide an indication of battery status (e.g. 40%
charge, 60% charge or 60 % discharge, 40 % discharge). In an embodiment, the processor
407 of the drivable distance estimation unit 402 is the same as Engine control unit (ECU) of
the battery-operated vehicle. In another embodiment, the processor 407 of the drivable
distance estimation unit 402 is a dedicated processor which is operatively coupled with the
ECU of the battery-operated vehicle.
[0042] In an embodiment of the present invention, all the parameters required for
range estimation may take real-time values for range estimation.
[0043] In another embodiment of the present invention, only real time value of
battery power and rolling resistance is considered for range estimation. The value of the tire
pressure is sensed every minute and passed to the processor for further processing of rolling
resistance and to estimate the drivable distance. Thus, the estimation of drivable distance
provided by the present invention will be most accurate.
[0044] In yet another embodiment of the present invention, the value of the tire
pressure is sensed periodically and passed to the processor for further processing of rolling
resistance and to estimate the drivable distance.
[0045] In yet another embodiment of present invention, aerodynamic resistance is
measured in real time and used for computing the range estimation.

[0046] It would be appreciated that any of the foregoing may be implemented in the
form of software, hardware and/or firmware. Further, these functionalities may be
implemented using a Controller, an application specific integrated circuit (ASIC), an
electronic circuit, a processor (shared, dedicated, or group) and memory that execute one or
more software instructions and/or other suitable logic or components that provide the
described functionality.
[0047] As would be apparent to those skilled in the art, the disclosed techniques can
be used with any type of communication. Further, according to an aspect of the present
disclosure, the disclosed techniques are performed to provide an accurate estimation of
drivable distance that can be covered by a battery operated vehicle with the available battery
capacity at a particular instant of time. This feature enables the driver of the battery-operated
vehicle to well plan his journey.
[0048] The language used in the specification has been principally selected for
readability and instructional purposes, and it may not have been selected to delineate or
circumscribe the inventive subject matter. It is therefore intended that the scope of the
disclosure be limited not by this detailed description, but rather by the following claims.
Accordingly, the disclosure of the embodiments is intended to be illustrative, but not limiting,
of the scope, which is set forth in the following claims.
[0049] Although the present invention has been described in considerable detail
regarding figures and certain preferred embodiments thereof, other versions are possible.
Therefore, the scope of the present invention should not be limited to the description of the
preferred versions contained herein.

We Claim:
1. A system for estimating drivable distance for a battery-operated vehicle, said system
comprising:
at least one sensing unit comprising:
a sensor for sensing tire pressure value; and
a transmitter for transmitting the sensed tire pressure value;
and
a drivable distance estimation unit operatively coupled to the at least one sensing unit,
said drivable distance unit comprising:
a memory configured for storing a table, said table defining a mapping between a
plurality of tire pressure values and a plurality of rolling resistance coefficient values;
a receiver for receiving the at least one sensed tire pressure value; and
a processor configured for:
determining at least one rolling resistance coefficient value from the table
corresponding to the at least one sensed tire pressure value; and
estimating drivable distance based on the at least one determined rolling resistance
coefficient value.
2. The system as claimed in claim 1, wherein the drivable distance is estimated in
kilometers and wherein the processor is configured for estimating drivable distance based on
the at least one determined rolling resistance coefficient value by:
determining available battery energy (Eavailable);
determining battery energy consumption/kilometer (Econsumed); and
estimating drivable distance as a ratio of the available battery energy (Eavailable) and
battery energy consumption/kilometer (Econsumed).
3. The system as claimed in claim 2, wherein the processor is configured for determining
the battery energy consumption/kilometer (Econsumed) by:
determining power (Pacc) required to accelerate the battery-operated vehicle;
determining power (Proad-load) required to overcome aerodynamic drag force and
rolling friction force; and
determining the battery energy consumption/kilometer (Econsumed) as the summation of
(Pacc) and (Proad-load);

wherein (Pacc) is determined based on the following:
(Pacc)=M x a x v(t),
where M is the mass of the battery-operated vehicle, a is the acceleration of the vehicle and
v(t) is the instantaneous velocity; and
wherein (Proad-load) is determined based on the following:
(Proad-load) = Ftraction x v(t),
where Ftraction is summation of aerodynamic drag force (Faerodynamic) and rolling friction
force (Frolling), and v(t) is the instantaneous velocity of the battery-operated vehicle.
4. The system as claimed in claim 3, wherein the processor is configured for determining
the aerodynamic drag force by:
Faerodynamic =1/2 ρ v2 Cd A,
where ρ is air density, v is the speed of the vehicle, A is frontal area and Cd is the coefficient
of aerodynamic resistance.
5. The system as claimed in claim 3, wherein the processor is configured for determining
the rolling friction force (Frolling) by:
Frolling = μr.W,
where, μr is the rolling resistance coefficient of the vehicle determined from the table based
on the sensed tire pressure and W is the weight of the battery-operated vehicle.
6. The system as claimed in claim 1, wherein the processing unit is configured for
estimating drivable distance based on the at least one determined rolling resistance coefficient
value by:
performing summation of the at least one determined rolling resistance coefficient
value to determine a resultant rolling resistance coefficient value; and
estimating drivable distance based on the determined resultant rolling resistance
coefficient value.
7. The system as claimed in claim 1, wherein a value of the rolling resistance
corresponds to a value of the sensed tire pressure or a value of the rolling resistance
corresponds to a range of sensed tire pressure values.
8. A method for estimating drivable distance for a battery-operated vehicle, said method
comprising:

sensing at least one tire pressure value;
determining at least one rolling resistance coefficient value corresponding to the at
least one sensed tire pressure value from a table storing a mapping between a plurality of tire
pressure values and a plurality of rolling resistance coefficient values; and
estimating drivable distance based on the at least one determined rolling resistance
coefficient value.
9. The method as claimed in claim 8, wherein the drivable distance is estimated in
kilometers and wherein estimating drivable distance based on the at least one determined
rolling resistance coefficient value comprises:
determining available battery energy (Eavailable);
determining battery energy consumption/kilometer (Econsumed); and
estimating drivable distance as a ratio of the available battery energy (Eavailable) and
battery energy consumption/kilometer (Econsumed).
10. The method as claimed in claim 9, wherein determining the battery energy
consumption/kilometer (Econsumed) comprises:
determining power (Pacc) required to accelerate the battery-operated vehicle;
determining power (Proad-load) required to overcome aerodynamic drag force and
rolling friction force; and
determining the battery energy consumption/kilometer (Econsumed) as the summation of
(Pacc) and (Proad-load);
wherein (Pacc) is determined based on the following:
(Pacc)=M x a x v(t), where M is the mass of the battery-operated vehicle, a is the
acceleration of the vehicle and v(t) is the instantaneous velocity; and
wherein (Proad-load) is determined based on the following:
(Proad-load) = Ftraction x v(t), where Ftraction is summation of aerodynamic drag force
(Faerodynamic) and rolling friction force (Frolling), and v(t) is the instantaneous velocity of the
battery-operated vehicle.
11. The method as claimed in claim 10, wherein determining the aerodynamic drag force
comprises:
determining the aerodynamic drag force Faerodynamic based on:
Faerodynamic =1/2 ρ v2 Cd A,

where ρ is air density, v is the speed of the vehicle, A is frontal area and Cd is the coefficient
of aerodynamic resistance.
12. The method as claimed in claim 10, wherein determining the rolling friction force
(Frolling) comprises:
determining the rolling friction force (Frolling) based on:
Frolling = μr.W,
where, μr is the rolling resistance coefficient of the vehicle determined from the table based
on the sensed tire pressure and W is the weight of the battery-operated vehicle.
13. The system as claimed in claim 8, wherein estimating drivable distance based on the
at least one determined rolling resistance coefficient value comprises:
performing summation of the at least one determined rolling resistance coefficient
value to determine a resultant rolling resistance coefficient value; and
estimating drivable distance based on the determined resultant rolling resistance
coefficient value.
14. The system as claimed in claim 1, wherein a value of the rolling resistance
corresponds to a value of the sensed tire pressure or a value of the rolling resistance
corresponds to a range of sensed tire pressure values.