Claims:We claim:
1. A method (400) for providing an appropriate torque available to a vehicle, the method comprising:
estimating (402), by a Control Unit (CU) (101), a current mass of the vehicle;
calculating (404), by the CU (101), a road grade of a road where the vehicle is currently travelling by fusing an estimated road grade and a calculated road grade with varying weights;
determining (405), by the CU (101), a current condition of the road where the vehicle is currently travelling based on slosh in the fuel levels present in a fuel tank present in the vehicle;
determining (406), by the CU (101), road conditions ahead using a location sensing means (104);
estimating (408), by the CU (101), a required torque; and
providing (409), by the CU (101), the estimated required torque to the vehicle.
2. The method, as claimed in claim 1, wherein the calculated grade over a fixed span of time or a fixed span of distance depends on a gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance.
3. The method, as claimed in claim 1, wherein the estimated grade over a fixed span of time or a fixed span of distance depends on a force that is transferred to wheels of the vehicle from a powertrain of the vehicle, the speed of the vehicle, a rolling resistance of the vehicle, acceleration value of the vehicle for a specified period of time, an estimated mass of the vehicle, and an acceleration of the vehicle due to gravity.
4. The method, as claimed in claim 3, wherein the estimated mass of the vehicle depends on the force that is transferred to the wheels from the powertrain of the vehicle, a resistance value as force due to aerodynamic drag, the acceleration of the vehicle, a deceleration due to rolling resistance value, deceleration of the vehicle due to the vehicle climbing a grade; and real world resistance errors.
5. The method, as claimed in claim 4, wherein the method comprises using a filter for minimizing fluctuations in the estimated mass.
6. The method, as claimed in claim 1, wherein the weights are varied, by the CU (101), such that sum of the weights equals to 1.
7. The method, as claimed in claim 1, wherein the method further comprises using a filter for minimizing fluctuations in the calculated road grade of the road .
8. The method, as claimed in claim 1, wherein the method comprises communicating (410), by the CU (101), the estimated torque to the user using a user interface (105).
9. The method, as claimed in claim 1, wherein the method comprises providing, by the CU (101), a manual override means (106).
10. The method, as claimed in claim 1, wherein the method is a closed loop process.
11. A system (100) for providing an appropriate torque available to a vehicle, the system comprising a Control Unit (CU) (101) configured for:
estimating a current mass of the vehicle;
calculating a road grade of a road where the vehicle is currently travelling by fusing an estimated road and a calculated road grade with varying weights;
determining a current condition of the road where the vehicle is currently travelling based on slosh in the fuel levels present in a fuel tank present in the vehicle;
determining (406) road conditions ahead using a location sensing means (104);
estimating (408) a required torque; and
providing (409) the estimated required torque to the vehicle.
12. The system, as claimed in claim 11, wherein the CU (101) is configured for calculating (403) the calculated grade over a fixed span of time or a fixed span of distance, wherein the calculated grade depends on a gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance.
13. The system, as claimed in claim 11, wherein the CU (101) is configured for calculating (403) the estimated grade over a fixed span of time or a fixed span of distance, wherein the estimated grade depends on a force that is transferred to wheels of the vehicle from a powertrain of the vehicle, the speed of the vehicle, a rolling resistance of the vehicle, acceleration value of the vehicle for a specified period of time, an estimated mass of the vehicle, and an acceleration of the vehicle due to gravity.
14. The system, as claimed in claim 13, wherein the CU (101) is configured for estimating (402) the mass of the vehicle, wherein the estimated mass of the vehicle depends on the force that is transferred to the wheels from the powertrain of the vehicle, a resistance value as force due to aerodynamic drag, the acceleration of the vehicle, a deceleration due to rolling resistance value, deceleration of the vehicle due to the vehicle climbing a grade; and real world resistance errors.
15. The system, as claimed in claim 14, wherein the CU (101) is configured for using a filter for minimizing fluctuations in the estimated mass.
16. The system, as claimed in claim 11, wherein the CU (101) is configured for varying the weights such that sum of the weights equals to 1.
17. The system, as claimed in claim 11, wherein the CU (101) is configured for using a filter for minimizing fluctuations in the calculated road grade of the road.
18. The system, as claimed in claim 11, wherein the CU (101) is configured for communicating the estimated torque to the user using a user interface (105).
19. The system, as claimed in claim 11, wherein the CU (101) is configured for providing a manual override means (106).
, Description:TECHNICAL FIELD
Embodiments disclosed herein relate to managing torque available to a vehicle, and more particularly to providing an appropriate torque available to the vehicle based on prevailing conditions.
BACKGROUND
Fuel economy is a critical parameter for any vehicle. In an example, for a commercial vehicle, fuel expenses can constitute up to 50% of the operating expenses of the vehicle. There is also a variation in fuel economy depending on factors such as the driver, the road, the weather conditions and the vehicle.
A current solution provides a user with the option to select the mode manually. This is dependent on the user and the selection of the user can be based on his knowledge and this has limitations such as driver changes constantly, lack of awareness, and so on.
Another solution uses a load and grade sensor and a controller. This has limitations as the system requires a load sensor and a grade sensor, which may prove expensive. The signal from the grade sensor also has a lot of fluctuations due to noise and vibration from vehicle and road conditions.
OBJECTS
The principal object of embodiments herein is to disclose methods and system for providing an appropriate torque available to the vehicle based on prevailing conditions.
These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating at least one embodiment and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.
BRIEF DESCRIPTION OF FIGURES
Embodiments herein are illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
FIG. 1 depicts a system in a vehicle for providing an appropriate torque available to the vehicle based on prevailing conditions, according to embodiments as disclosed herein;
FIG. 2 depicts an example scenario for calculating the road grade, according to embodiments as disclosed herein;
FIG. 3 depicts an example torque map, according to embodiments as disclosed herein; and
FIG. 4 is a flowchart depicting the process of providing an appropriate torque available to the vehicle based on prevailing conditions, according to embodiments as disclosed herein.

DETAILED DESCRIPTION
The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
Embodiments herein may be described and illustrated in terms of blocks which carry out a described function or functions. These blocks, which may be referred to herein as units or modules or the like, are physically implemented by analog and/or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by firmware and/or software. The circuits may, for example, be embodied in one or more semiconductor chips, or on substrate supports such as printed circuit boards and the like. The circuits constituting a block may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuitry), or by a combination of dedicated hardware to perform some functions of the block and a processor to perform other functions of the block. Each block of the embodiments may be physically separated into two or more interacting and discrete blocks without departing from the scope of the disclosure. Likewise, the blocks of the embodiments may be physically combined into more complex blocks without departing from the scope of the disclosure.
The embodiments herein achieve methods and systems for providing an appropriate torque available to the vehicle based on prevailing conditions. Referring now to the drawings, and more particularly to FIGS. 1 through 4, where similar reference characters denote corresponding features consistently throughout the figures, there are shown embodiments.
The vehicle, as disclosed herein, can be any vehicle that uses any suitable fuel. Examples of the vehicle can be, but not limited to, cars, trucks, buses, vans, trains, aircraft, agricultural vehicles (such as, but not limited to, tractors, threshers, sowing machines, and so on), motorbikes, scooters, and so on.
FIG. 1 depicts a system in a vehicle for providing an appropriate torque available to the vehicle based on prevailing conditions. The system 100, as depicted, comprises a control unit (CU) 101, connected to one or more modules, such as an Engine Control Unit (ECU) 102, an Anti-Lock Braking System (ABS) controller 103, a location sensing means 104, a user interface 105, at least one manual override means 106, and at least one memory 107. In an embodiment herein, the CU 101 can be connected to the one or more modules using a wired means (such as a Controller Area Network (CAN) bus). In an embodiment herein, the CU 101 can be connected to the one or more modules using a wireless means (such as a Wi-Fi, Bluetooth, Bluetooth Low Energy (BLE), Wi-Fi Direct, GSM, 4G and so on).
In an embodiment herein, the CU 101 can be a dedicated unit. In an embodiment herein, the functions of the CU 101 can be integrated with one or more other control units present in the vehicle, such as the ECU 102.
The location sensing means 104 can be a means for determining the location of the vehicle. The location sensing means 104 can be used for determining the current altitude of the vehicle. The location sensing means 104 can use a suitable location(system/method) such as a Global Positioning System (GPS), Simultaneous GPS (S-GPS), triangulation, Galileo, GAGAN, an inertial navigation system, a Wide Area Augmentation System (WAAS), Local Area Augmentation System (LAAS)/Ground-Based Augmentation System (GBAS), a Local Positioning System (LPS), and so on. In an embodiment herein, the location sensing means 104 can be a dedicated unit. In an embodiment herein, the location sensing means 104 can be a generic unit/device (such as a mobile device, smart phone, a tablet, and so on).
The user interface 105 can be a means for the CU 101 to interface with the user. Examples of the user interface 105 can be, but not limited to, an instrument cluster, a vehicle infotainment system, a user device (such as a mobile phone, smart phone), one or more switches, an On-Board Diagnostics (OBD) port, and so on.
The manual override means 106 can enable a user to override the control unit 101. Examples of the manual override means 106 can be, but not limited to, a switch, an instrument cluster, a vehicle infotainment system, a user device (such as a mobile phone, smart phone), one or more switches, an On-Board Diagnostics (OBD) port, and so on.
The CU 101 can comprise of a road grade estimation module 101a, a mass estimation module 101b, and a controller 101c. The CU 101 can receive information from the other modules such as speed of the vehicle, current engine torque, torque being demanded by the driver, gear status, current fuel level, current fuel consumption rate, wheel speed, and location of the vehicle (which can be in terms of latitude and longitude, altitude of the vehicle, and so on).
The mass estimation module 101b can estimate the current mass of the vehicle. The current mass of the vehicle can depend on the force that is transferred to the wheels from the powertrain of the vehicle, a resistance value as force due to aerodynamic drag, the acceleration of the vehicle, a deceleration due to rolling resistance value, deceleration of the vehicle due to the vehicle climbing a grade; and real world resistance errors. In an example herein, the mass estimation module 101b can estimate the mass of the vehicle (MassEst) using Distance based moving average calculation for Torque, Elevation (Road Grade), Rolling Resistance and Acceleration as the difference between the force that is transferred to the wheels from the powertrain of the vehicle and the resistance value as force due to aerodynamic drag divided by the sum of acceleration of the vehicle, the resistance value as force due to aerodynamic drag and also converted as a deceleration due to rolling resistance value normalized to estimated mass; the deceleration of the vehicle due to the vehicle climbing a grade; and the correction applied to compensate for real world resistance errors which can be calculated from vehicle tests and aging of the vehicle. The above is represented as follows:
mass of the vehicle= ([F_powertrain-F_aero])/¦([acceleration+decceleration@rollingresistance+@decceleration@grade+lossesfactor])
Where
F_powertrain is the force that is transferred to the wheels from the powertrain of the vehicle;
F_aero is the resistance value as force due to aerodynamic drag;
decceleration@rollingresistance is the resistance value as force due to aerodynamic drag and also converted as a deceleration due to rolling resistance value normalized to estimated mass;
decceleration@grade is the deceleration of the vehicle due to the vehicle climbing a grade; and
lossesfactor is the correction applied to compensate for real world resistance errors and can be calculated from vehicle tests and aging of the vehicle.
The mass estimation module 101b can use a filter (such as a Kalman filter) for minimizing fluctuations (if any) in the estimated mass.
The road grade estimation module 101a can calculate the road grade using a trigonometric function of inverse sine of hypotenuse upon opposite side. Road profile represents a right-angle triangle and the road is the hypotenuse side of the triangle with the opposite side being the vertical climb (as depicted in the example in FIG. 2). The road grade estimation module 101a can estimate an estimated grade and a calculated grade at different sampling rates.
The road grade estimation module 101a can determine the calculated grade over a fixed span of time or a fixed span of distance, wherein the calculated grade over the fixed span of time or the fixed span of distance depends on a gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance. In an example herein, the road grade estimation module 101a can determine the calculated grade over a fixed span of time or a fixed span of distance as the product of the gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance and the conversion factor of degrees to radians and the degree grade to percentage grade where 45 Degrees=100% Grade divided by the square root of the difference between the squares of the gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance and a square of a gain in distance that the vehicle achieves over the fixed span of time or the fixed span of distance.
GradeCalculated = (Verticaldistancetravelled*57.22*2.22 )/v([(horizontaldistancetravelled)^2-?(verticaldistancetravelled)?^2])
Grade estimated is the estimated average grade of the vehicle from a location sensing means (such as GPS) calculated for a fixed span of distance or time. The estimated grade over a fixed span of time or a fixed span of distance can depend on the force that is transferred to wheels of the vehicle from a powertrain of the vehicle, the speed of the vehicle, the rolling resistance of the vehicle, acceleration value of the vehicle for a specified period of time, an estimated mass of the vehicle, and an acceleration of the vehicle due to gravity.
In an example herein, the road grade estimation module 101a can determine the estimated grade over a fixed span of time or a fixed span of distance as the difference between the force that is transferred to the wheels of the vehicle from the powertrain of the vehicle and the product of the rolling resistance value from coast down trails and the square of the speed, the rolling resistance of the vehicle, and the product of the averaged out acceleration value for a specified period of time and the estimated mass of the vehicle divided by the product of the estimated mass of the vehicle and the acceleration of the vehicle due to gravity. The rolling resistance can be a function of the velocity of the vehicle and the estimated mass of the vehicle.
Grade estimatedated= ¦((F_powertrain-0.255*?Speed?^2-rollingresistance-@Accelerationmean*MassEst))/(MassEst*(9.81))
rollingresistance=function(velocity,massEst)
Where
Accelerationmean is the averaged out acceleration value for a specified period of time which is calibratable. This is done to avoid any spikes in acceleration values due to harsh vehicle transitions;
Verticaldistancetravelled is the gain in height that the vehicle achieves over the fixed span of time or the fixed span of distance;
horizontaldistancetravelled is the gain in distance that the vehicle achieves over the fixed span of time or the fixed span of distance;
57.22 is the conversion factor of degrees to radians;
2.22 is degree grade to percentage grade where 45 Degrees=100% Grade;
0.255 is the aerodynamic drag coefficient from coast down trails; and
9.81 is the acceleration due to gravity.
The estimated grade and the calculated grade can be fused into a single value (hereinafter referred to as ‘grade’) with varying weights for each of the estimated grade and the calculated grade. Varying weights refers to different values of mass estimates at multiple instances, where these instances are filtered using a Kalman filter and a smoother and stable vehicle mass is obtained from them. The grade fusing is done by multiplying weights to the calculated and estimated gradient such that sum of the weights equals to 1. An initially calculated grade is given more weightage due to absence of a mass estimate and then after estimated grade is given more weight.
The road grade estimation module 101a can use a filter (such as a Kalman filter) for minimizing fluctuations (if any) in the road grade.
The mass estimation module 101b and the road grade estimation module 101a can provide the estimated mass and grade to the controller 101c. The controller 101c can determine the current condition of the road based on slosh in the fuel levels present in the fuel tank of the vehicle. The controller 101c can determine the road conditions ahead (such as gradient, traffic conditions, and so on), based on the information from the location sensing means 104. The controller 101c can also fetch the user history (such as the driving habits of the user, preferred routes, and so on) from a suitable location such as the memory 107. The controller 101c can also receive information such as current fuel levels, current torque, and so on.
Based on the above received and determined information, the controller 101c can estimate the required torque, based on one or more user criteria. Torque is estimated using engine speed and fueling as inputs to a set of predefined maps which are calibrated during the engine dynamometer trails. An example of the criteria can be, but not limited to, a current selected driving mode.
The controller 101c can calculate the torque using the fuel injected using the following base formula:
Torque=(quantity of fuel injected*number of cylinders in the engine)*1.5
The controller 101c can correlate the values, by doing tests at an engine dynamometer. The test can be performed in a test chamber designed to measure engine torque and emissions. The tests can comprise of measuring the engine torque and saving the measured torque as a map (as depicted in the example in FIG. 3) at the engine test bed.
In the example depicted in the map, the torque range can be from 0 to the maximum torque (which can be the user defined torque) in pre-defined steps (such as, 25 Nm). In the example depicted in the map, the speed range can be from a lower threshold (for example, 1000 rpm (revolutions per minute)) to Full Load rpm in pre-defined steps (such as, 200 rpm). The map can comprise of three parameters: engine speed on the X-axis, torque command from the quantity of fuel injected on the Y-axis, and the measured engine torque from the dynamometer on the Z-axis.
The controller 101c can make the required torque available to the vehicle, either directly or via another unit (such as the ECU 102), which can adjust the available torque accordingly. In an embodiment herein, the controller 101c can communicate the required torque to the user, using one or more user interfaces 105.
The above mentioned embodiments herein are a close looped process, wherein the required torque is compared to the vehicle acceleration data.
The memory 107 includes storage locations to be addressable through one or more of the modules. The memory 107 can be a volatile memory and/or a non-volatile memory. Further, the memory 107 can include one or more computer-readable storage media. The memory 107 may include non-volatile storage elements. For example, non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. In some examples the memory 107 can be configured to store data received from the modules and data estimated by the CU 101. In an embodiment herein, the memory 107 can be integrated with one or more of the modules, such as the CU 101, the ECU 102, and so on. In an embodiment herein, the memory 107 can be an independent module.
FIG. 4 is a flowchart depicting the process of providing an appropriate torque available to the vehicle based on prevailing conditions. The CU 101 receives (401) information from the other modules such as speed of the vehicle, current engine torque, torque being demanded by the driver, gear status, current fuel level, current fuel consumption rate, wheel speed, and location of the vehicle (which can be in terms of latitude and longitude, altitude of the vehicle, and so on). The CU 101 estimates (402) the current mass of the vehicle using distance based moving average calculation for Torque, Elevation (Road Grade), Rolling Resistance and Acceleration. In an embodiment herein, the CU 101 can use a filter (such as a Kalman filter) for minimizing fluctuations (if any) in the estimated mass.
The CU 101 calculates (403) the estimated road grade and the calculated road grade. The CU 101 can estimate an estimated grade and a calculated grade at different sampling rates. The CU 101 estimates (404) the road grade by fusing the estimated road grade and the calculated road grade with varying weights for each of the estimated grade and the calculated grade. In an embodiment herein, the CU 101 can use a filter (such as a Kalman filter) for minimizing fluctuations (if any) in the calculated grade.
The CU 101 determines (405) the current condition of the road based on slosh in the fuel levels present in the fuel tank. The CU 101 determines (406) the road conditions ahead, based on the information from the location sensing means 104. The CU 101 also receives/fetches (407) information such as the user history (such as the driving habits of the user, preferred routes, and so on), current fuel levels, current torque, and so on.
Based on the above received and determined information, the CU 101 estimates (408) the required torque, based on one or more user criteria. The CU 101 provides (409) the required torque to the vehicle, either directly or via another unit (such as the ECU 102), which can adjust the available torque accordingly. In an embodiment herein, the CU 101 communicates (410) the required torque to the user, using one or more user interfaces 105. The various actions in method 400 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 4 may be omitted.
Embodiments herein do not require additional sensor(s) to calculate mass and grade thus making it frugal and ensuring that the fuel economy of the vehicle is improved.
The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The network elements shown in FIG. 1 include blocks which can be at least one of a hardware device, or a combination of hardware device and software module.
The embodiment disclosed herein describes methods and systems for providing an appropriate torque available to the vehicle based on prevailing conditions. Therefore, it is understood that the scope of the protection is extended to such a program and in addition to a computer readable means having a message therein, such computer readable storage means contain program code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The method is implemented in at least one embodiment through or together with a software program written in e.g. Very high speed integrated circuit Hardware Description Language (VHDL) another programming language, or implemented by one or more VHDL or several software modules being executed on at least one hardware device. The hardware device can be any kind of portable device that can be programmed. The device may also include means which could be e.g. hardware means like e.g. an ASIC, or a combination of hardware and software means, e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. The method embodiments described herein could be implemented partly in hardware and partly in software. Alternatively, the invention may be implemented on different hardware devices, e.g. using a plurality of CPUs.
The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of embodiments and examples, those skilled in the art will recognize that the embodiments and examples disclosed herein can be practiced with modification within the spirit and scope of the embodiments as described herein.