Claims:We claim:
1. A method for optimizing energy consumption of an electric vehicle, the method comprising:
Collecting, by a first set of sensors, a first set of input factors from a plurality of vehicle parts wherein each of the vehicle parts has at least one corresponding sensor from the first set of sensors;
Collecting, by a second set of sensors, a second set of input factors;
Determining, by an efficiency controller, the optimum input or output driving parameters of the electric vehicle comprising steps of;
Calculating, using the first set of input factors, an actual energy consumption;
Determining, using the second set of input factors, a target range;
Calculating, a target energy consumption value based on the target range and at least one of the second input factors and at least one of the first input factors;
Calculating the optimum input or output driving parameters based on the target energy consumption; and
Regulating, by the efficiency controller, a plurality of vehicle driving parameters, based on the optimum input/output driving parameters of the electric vehicle.
2. The method of claim 1, wherein the first set of input factors include any one or a combination of battery state of charge (SoC), battery voltage, battery current, motor RPM, vehicle speed, vehicle acceleration, road slope, input steering angle, throttle position, brake lever position, motor temperature, battery temperature, and tire pressure.
3. The method of claim 1, wherein the second set of input factors include anyone of a distance target by user input, distance target by vehicle mode, and total battery energy capacity of the vehicle.
4. The method of claim 2, wherein the at least one of the first input factors is battery SoC.
5. the method of claim 3, wherein the at least one of the second input factors is total battery energy capacity of the vehicle.
6. The method of claim 1, the first set of sensors are current sensors, tire pressure sensors, temperature sensors, voltage sensors, gyroscope, accelerometers, and RPM sensors.
7. The method of claim 1, wherein the plurality of vehicle driving parameters include anyone or a combination of motor torque, battery output power, motor input power, motor output power, and battery and motor current.
8. The method of claim 1, wherein the target range is determined dynamically.
9. The method of claim 8, wherein the target range is determined based on a user input of target distance.
10. The method of claim 8, wherein the target range is determined based on health of the vehicle.
11. The method of claim 10, wherein the health of the vehicle includes anyone or a combination of tire pressure, state of health of a battery, and accelerator health.
12. The method of claim 1, further comprises dynamically adjusting the target energy consumption.
13. The method of claim 12, wherein the dynamically adjusting is based on battery age, battery capacity, or State of health of a battery.
14. The method of claim 1, wherein configuration of the efficiency controller is dynamically controlled during a drive of the vehicle.
15. The method of claim 1, further comprising adjusting regenerative braking based on the target energy consumption and the target range.
16. The method of claim 15, wherein the adjusting of regenerative braking is based on anyone or the combination of the first set of input factors or the second set of input sensors.
17. The method of claim 1, wherein the vehicle is an electric vehicle, or a hybrid vehicle.
18. A system configured to implement the method as claimed in any of the claims 1-17.
, Description:FIELD OF THE DISCLOSURE
[001] The present disclosure is generally related to optimizing vehicle energy consumption and more particularly, the present disclosure is related to the determination of an optimum input/output driving parameters of an electric vehicle.
BACKGROUND
[002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[003] The range of electric vehicles has been a point of concern for various years with EV manufacturers. The range of the EVs depends on various factors like battery charge available, way the EV is driven, health of the battery, road conditions, etc. Consistency in Range automatically makes the riding & charging pattern a lot more predictable by letting the users arrive at the exact Range target they have throughout a ride/drive. Consistent Range is the ability to achieve a Range greater than or equal to a pre-set Range target (wide spectrum) irrespective of noise factors like driver aggression, traffic conditions, road slope, tire inflation levels, battery age, etc.
[004] Current solutions targeting the range are inefficient and do not include the current status of the EV. Therefore, there is a requirement for a solution to provide more efficient control over the range and making the range a consistent feature for EVs

BRIEF SUMMARY
[005] It will 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 to describe the particular versions or embodiments only, and is not intended to limit the scope of the present disclosure.
[006] In an example embodiment, a method for optimizing energy consumption of an electric vehicle is disclosed. The method includes collecting, by a first set of sensors, a first set of input factors from a plurality of vehicle parts wherein each of the vehicle parts has at least one corresponding sensor from the first set of sensors, collecting, by a second set of sensors, a second set of input factors; determining, by an efficiency controller, the optimum input or output driving parameters of the electric vehicle comprising steps of; calculating, using the first set of input factors, an actual energy consumption, determining, using the second set of input factors, a target range, calculating, a target energy consumption value based on the target range and at least one of the second input factors and at least one of the first input factors; , calculating the optimum input or output driving parameters based on the target energy consumption, and regulating, by the efficiency controller, a plurality of vehicle driving parameters, based on the optimum input/output driving parameters of the electric vehicle.
BRIEF DESCRIPTION OF THE DRAWINGS
[007] The accompanying drawings illustrate various embodiments of systems, methods, and embodiments of various other aspects of the disclosure. Any person with ordinary skills in the art will appreciate that the illustrated element boundaries (e.g. boxes, groups of boxes, or other shapes) in the figures represent one example of the boundaries. It may be that in some examples one element may be designed as multiple elements or that multiple elements may be designed as one element. In some examples, an element shown as an internal component of one element may be implemented as an external component in another and vice versa. Furthermore, elements may not be drawn to scale. Non-limiting and non-exhaustive descriptions are described with reference to the following drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating principles.
[008] FIG. 1A illustrates a block diagram of a system 100 for determining optimum input/output driving parameters of an electric vehicle, according to an embodiment of the invention;
[009] FIG. 1B illustrates a block diagram of an efficiency controller 102 and its internal configuration, according to an embodiment of the invention;
[0010] FIG. 2A-2B illustrates a method for calculating the optimum input/output driving parameters of an electric vehicle, according to an embodiment of the invention.

DETAILED DESCRIPTION
[0011] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “comprising,” “having,” “containing,” and “including,” and other forms thereof, are intended to be equivalent in meaning and be open-ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items.
[0012] It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the preferred, systems and methods are now described.
[0013] Embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings in which like numerals represent like elements throughout the several figures, and in which example embodiments are shown. Embodiments of the claims may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. The examples set forth herein are non-limiting examples and are merely examples among other possible examples.
[0014] FIG. 1 illustrates a system 100 for determining optimum input/output driving parameters for driving of an electric vehicle (EV), according to an embodiment of the invention. The system 100 includes an efficiency controller 102, a first set of sensors 104A-104E (cumulatively referred to as first set of sensors 104), a second set of sensors 106A-106C (cumulatively referred to as second set of sensors 106) and a vehicle driving part 108.
[0015] According to an embodiment of the invention, the efficiency controller 102 is a processor. The efficiency controller 102 may be a single-core or multiple-core processor configured to handle various other control functions of the EV. The efficiency controller 102 may be a dedicated/standalone processor or a shared processor to share other controlling functions of the EV.
[0016] The first set of sensors 104 may be any one of a current sensors, tire pressure sensors, temperature sensors, voltage sensors, gyroscope, accelerometers, and RPM sensors, etc. These first set of sensors 104 are configured to collect the first set of input factors from a plurality of parts of the EV. In an embodiment of the invention, the first set of inputs may be battery state of charge (SoC), battery voltage, battery current, motor RPM, vehicle speed, vehicle acceleration, road slope, input steering angle, throttle position, brake lever position, motor temperature, battery temperature, and tire pressure, etc.
[0017] The second set of sensors 106 may be any one of a touch screen input sensor or battery energy capacity sensor configured to collect a second input factors. The second input factors may be any one of a distance target by user input, distance target by vehicle mode, and total battery energy capacity of the EV.
[0018] According to an embodiment of the invention, the vehicle driving part 108 may be a motor that controls the driven characteristics of the EV.
[0019] The efficiency controller 102 is configured to be communicably connected to the first sets of sensors 104 and the second set of sensors 106. The efficiency controller 102, receives information gathered by the first set of sensors 104 and the second set of sensors 106 and calculates “on the fly” optimum input/output driving parameters to be provided to the vehicle driving part 108 to function.
[0020] Fig. 1B illustrates a block diagram of the efficiency controller 102 and its internal configuration, in accordance with an embodiment of the invention. The efficiency controller 102 includes an Energy consumption calculator (ECCC) 1024, a target energy calculator (TEC) 1022, and a vehicle efficiency regulator (VER) 1026.
[0021] It is to be noted that the TEC 1022, ECC 1024, and VER 1026 may be hardware modules provided within the efficiency calculator 102.
[0022] However, it is to be appreciated that the TEC 1022, ECC 1024 and VER 1026 modules may also be software modules based on instructions fetch by the efficiency controller 102 from a local memory (not disclosed in the figure).
[0023] The ECC 1024 receives data from the first set of sensors 104 and calculates actual energy consumption. Whereas, the TEC 1022 receives data from the second set of sensors 106 and determines a target range and further calculates the target energy consumption. The target energy consumption is determined by the TEC 1022 using the target range and a battery SoC i.e. one of the first input factors acquired by the TEC 1022 from the ECC 1024, and the total battery energy capacity of the EV i.e. one of the second input factors.
[0024] The VER 1026, receives the target energy consumption and the actual energy consumption and calculates the optimum input/output driving parameters for working of the EV to achieve a constant range.
[0025] Now referring to Fig. 2A, illustrating a flow chart of a method 200 to determine optimum input/output driving parameters for driving the EV, in accordance with an embodiment of the invention. It is to be noted that some steps may be replaced with each other and do not form an exact methodology of working of method 200.
[0026] At step 202, the first set of sensors gather various data from the plurality of vehicle parts necessary i.e. the first set of input factors, to calculate the optimum input/output driving parameters for the EV. The first set of input factors, as discussed above, may be battery state of charge (SoC), battery voltage, battery current, motor RPM, vehicle speed, vehicle acceleration, road slope, input steering angle, throttle position, brake lever position, motor temperature, battery temperature, and tire pressure. The first set of input factors are fed to the efficiency controller 102 for further computation.
[0027] At step 204, the second set of sensors gather the second set of input factors like distance target by user input, distance target by vehicle mode, and total battery energy capacity of the vehicle, etc. The second set of input factors are also forwarded to the efficiency controller 102 for further computation.
[0028] At step 206, the efficiency controller 102, determines the optimum input or output driving parameters for the EV using the first and second sets of input parameters. Referring to Fig. 2B, illustrating a further breakdown of step 206 of method 200.
[0029] At step 2062, the ECC 1024 calculates the actual energy consumption for the EV. This value is based on the various parameters as described above. The actual energy consumption means the efficiency at which the EV is currently running at.
[0030] At step 2064, the TEC 1022 determines the target range. The TEC 1022 calculates the target energy consumption by using the target range and a battery SoC i.e. one of the first input factors acquired by the TEC 1022 from the ECC 1024, and the total battery energy capacity of the EV i.e. one of the second input factors. . The target range may be the distance to be travelled by the EV.
[0031] At step 2068, the optimum input or output driving parameters of the EV is determined by using the target energy consumption and the actual energy consumption by the VER 1026.
[0032] Now, referring back to Fig. 2A, at step 208, the VER 1026 is configured to regulate the optimum input or output driving parameters by controlling a plurality of vehicle driving parameters. The plurality of vehicle driving parameters may be any one or a combination of motor torque, battery output power, motor input power, motor output power, and battery and motor current, etc.
[0033] In an exemplary operation, when a user inputs, through a touch screen, a distance to destination i.e. the target range, the user input is captured by the second set of sensors 106 (i.e. touch screen sensor) and fed to the TEC 1022.
[0034] Furthermore, the ECC 1024 receives information about the condition of the EV like battery state of charge (SoC), battery voltage, battery current, motor RPM, vehicle speed, vehicle acceleration, road slope, input steering angle, throttle position, brake lever position, motor temperature, battery temperature, and tire pressure from the first set of input sensors 104.
[0035] The TEC 1022 calculates the target energy consumption of the EV based on the target range and a battery SoC i.e. one of the first input factors acquired by the TEC 1022 from the ECC 1024, and the total battery energy capacity of the EV i.e. one of the second input factors.
[0036] The VER 1026, calculates optimum input or output driving parameters, from the target energy consumption and the actual energy consumption, that could be drawn by the vehicle driving part 108 like motor and regulates that the optimum input or output driving parameters are maintained, while the EV is used to achieve the distance to destinationbased on the user input. For example, if the user wants to achieve 50 km range, the ECC 1024 calculates the actual energy consumption value per distance travelled. Thereafter, the TEC 1022 determines the target range through user input (i.e. 50KM). Also, the TEC 1022 determines what should be the target energy consumption per distance, using the target range, battery SoC and the total battery energy capacity of the EV, in order to achieve the range of 50km. The VER 1026, regulates the motor or battery input and output parameters to maintain energy consumption within the target energy consumption. . Therefore, the VER 1026 limits the maximum torque, and the EV is not able to draw more than this value to achieve the distance to destination as input by the user. The VER 1026 checks that the motor 108 does not generate more torque and hence limits current and voltage from a battery to the motor 108.
[0037] According to an embodiment of the invention, the target range may be provided by a user or automatically calculated based on a manufactured given value and health of the EV.
[0038] According to another embodiment of the invention, the target energy consumption may be dynamically calculated during the drive. The dynamic calculation may be achieved using the first set of sensors 104 or the second set of sensors 106. For example, the efficiency controller 102 could gather information from the first set of sensors 104 that the user is trying to accelerate up a slope, thereby increasing the target consumption dynamically to achieve that slope climb. Also, the efficiency controller 102 may determine that the user has fed an input to decrease speed due to a downward slope or crowded area. Hence, in such a condition, the target energy consumption value may be decreased “on the fly” by the efficiency controller 102.
[0039] This is provided so as to meet varied modes which the EV may experience during the ride. For e.g. If the EV is currently operating in a mode where the output torque or battery power is limited in order to meet the target energy consumption however, if there's a sudden requirement of high torque or power to either negotiate an increasing slope or an over take another vehicle, the efficiency controller 102 is dynamically configured to output higher power for a small period during that event in order to safely complete the event.
[0040] According to another embodiment of the invention, regenerative braking may also be adjusted based on the target energy consumption and the target range to complement the optimum input or output driving parameters for the vehicle. The first set of sensors 104 and the second set of sensors 106 may be utilized manually or automatically to regulate the adjustment of regenerative braking. According to an example, a user may decide to enable or disable regenerative braking by providing an input through a touch screen i.e. a second set of sensors 106. Once enabled, based on a throttle and brake inputs, as captured by the first set of sensors, adjusting of regenerative braking is performed based on the target energy consumption and the actual energy consumption in order to complement the optimum input/output driving parameters.
[0041] The foregoing embodiments are described in sufficient detail to enable those skilled in the art to make and use the invention, and it is to be understood that other embodiments would be evident based on the present disclosure and that process or mechanical changes may be made without departing from the scope of the present invention.
[0042] In the foregoing description, numerous specific details are given to provide a thorough understanding of the invention. However, it will be apparent that the invention may be practiced without these specific details. In order to avoid obscuring the present invention, some well-known circuits, system configurations, and process steps are not shown in detail and would be understood by anyone having skill in the relevant art.
[0043] Likewise, the drawings showing embodiments of the apparatus/device are semi-diagrammatic and not to scale and, particularly, some of the dimensions are for the clarity of presentation and may be shown greatly exaggerated in the drawings.
[0044] While the invention has been described in conjunction with a specific preferred embodiment which is considered to be the best mode, it is to be understood that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the foregoing description and accompanying drawings. Accordingly, it is intended to embrace all such alternatives, modifications, and variations that fall within the scope of the included claims. All matters hithertofore set forth herein or shown in the accompanying drawings are to be interpreted in an illustrative and non-limiting sense.