Description:SYSTEM AND METHOD FOR MANAGING TORQUE IN MOTOR-ASSISTED VEHICLES

Field of the Invention
The present invention generally relates to automobiles and more particularly to a system and method for managing torque in motor-assisted vehicles.
Background
Conventionally, internal combustion engine (ICE)-based vehicles have been dominant in the automobile industry, with everything from commercial vehicles such as trucks and buses to personal vehicles such as scooters and cars employing ICEs for generating operational power to drive the vehicles. In recent years, however as global warming has been brought into the attention of general global population and people are striving towards building a sustainable and eco-friendly world to live in, ICE-based vehicles will be gradually replaced by vehicles employing renewable sources of energy, including electric vehicles, vehicles employing hydrogen cells and the like.
Generally, electric vehicles are still limited by an energy storage capacity of batteries employed within the vehicles that provide operational power to drive the vehicles. Consequently, an energy that is supplied from the battery to a motor of the electric vehicles needs to be judiciously conserved such that a high operating performance can be achieved. However, as electric vehicles may still be driven by drivers that are accustomed to driving ICE-based vehicles, such vehicles may be driven at high torque demands even when there is no requirement for such high torque demands to be provided to the motor of the electric vehicles (for example, when the electric vehicles are driven on flat roads with a low amount of load carried on the vehicle). Consequently, the energy that is provided from the batteries of such electric vehicles is high, leading to low operating performance of the electric vehicles.
Therefore, there is an urgent need for systems and methods that enable conservation of energy supplied from batteries of the electric vehicles through management of torque supplied to the motors of the electric vehicles.
 
Objects of the Invention
An object of the present invention is to provide a system and a method for managing torque in motor-assisted vehicles.
Another object of the present invention is to reduce consumption of electrical charge stored in batteries of motor-assisted vehicles.
Yet another object of the present invention is to increase a range of the motor-assisted vehicles in a single charge of the motor-assisted vehicles.
Still another object of the present invention is to improve a performance of motor-assisted vehicles.
Summary
The present invention generally relates to automobiles and more particularly to a system and method for managing torque in motor-assisted vehicles.
In an aspect, the present disclosure provides a system to manage torque in a motor-assisted vehicle. The system comprises a battery pack, a motor, a torque estimator adapted to estimate an actual torque generated by the motor, an input unit adapted to receive a driving parameter associated with the motor-assisted vehicle and a motor control device. The motor control device is configured to determine a change in the driving parameter based on the driving parameter received by the input unit; determine a demanded torque based on the determined change in the driving parameter; and determine a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
In one aspect of the invention, the driving parameter is selected from a driving mode, a change in throttle position, a load applied on the motor-assisted vehicle, an operating parameter associated with the battery pack and a road gradient.
In yet another aspect of the invention, the battery pack comprises multiple cells and the operating parameter associated with the battery pack is selected from a state of charge (SoC) of the battery pack, a state of health (SoH) of the battery pack, a temperature of the battery pack, a current associated with the battery pack, a voltage associated with the battery pack, a current associated with the each of the cell of the battery pack and a voltage associated with the each of the cell of the battery pack.
In still another aspect of the invention, the motor control device comprises a memory configured to store a mapping curve associated with the rate of change of torque corresponding to the actual torque.
In yet another aspect of the invention, the memory is configured to store a corresponding mapping curve for each driving mode of multiple driving modes in the motor-assisted vehicle.
In yet another aspect of the invention, the motor control device utilizes a machine-learning algorithm to determine the adjusted torque reference.
In another aspect, the present disclosure provides a method for managing torque in a motor-assisted vehicle. The method comprising estimating an actual torque generated by a motor of the motor-assisted vehicle, receiving a driving parameter associated with the motor-assisted vehicle, determining a change in the driving parameter based on the received driving parameter, determining a demanded torque based on the determined change in the driving parameter and determining a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
In one aspect of the invention, the driving parameter is selected from a driving mode, a change in throttle position, a load applied on the motor-assisted vehicle, an operating parameter associated with the battery pack and a road gradient.
In yet another aspect of the invention, the method comprises storing a mapping curve associated with the rate of change of torque corresponding to the actual torque.
In still another aspect of the invention, the method comprises storing a corresponding mapping curve for each driving mode of multiple driving modes in the motor-assisted vehicle.
In yet another aspect, the present disclosure provides a motor control device to manage torque in a motor-assisted vehicle. The device comprises a memory configured to store multiple executable instructions and a processor operably coupled to the memory and operable to execute the multiple executable instructions to estimate an actual torque generated by a motor of the motor-assisted vehicle, receive a driving parameter associated with the motor-assisted vehicle, determine a change in the driving parameter based on the received driving parameter, determine a demanded torque based on the determined change in the driving parameter, and determine a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
Brief Description of the Drawings
FIG. 1 shows a schematic view of a system to manage torque in a motor-assisted vehicle according to an embodiment of the present disclosure;
FIG. 2 shows a mapping curve associated with the δΤ/δt corresponding to the ΤE as per an embodiment of the present disclosure;
FIG. 3 shows a graph illustrating mapping curves for each driving mode of multiple driving modes in the motor-assisted vehicle according to an embodiment of the present disclosure;
FIG. 4 shows a flowchart illustrating steps of a method for managing torque in a motor-assisted vehicle as per an embodiment of the present disclosure;
FIG. 5 shows a block diagram of an exemplary operation of a system (such as the system shown in FIG. 1) according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram illustrating a motor control device to manage torque in a motor-assisted vehicle as per an embodiment of the present disclosure;
FIG. 7 shows a table illustrating correlation between torque, torque ramp rate, speed and mechanical power over time for a single driver using the motor-assisted vehicle as per an embodiment of the present disclosure;
FIG. 8 shows a table illustrating correlation between torque, torque ramp rate, speed and mechanical power over time for a single driver using the motor-assisted vehicle as per another embodiment of the present disclosure;
FIG. 9 shows a table illustrating correlation between torque, torque ramp rate, speed and mechanical power over time for a driver operating using the motor-assisted vehicle with a pillion rider or with additional payload according to an embodiment of the present disclosure;
FIG. 10 shows a table illustrating correlation between torque, torque ramp rate, speed and mechanical power over time for a driver operating using the motor-assisted vehicle with a pillion rider or with additional payload according to an embodiment of the present disclosure;
FIG. 11 shows a table illustrating correlation between torque, torque ramp rate and speed over time for a change in operating mode of the motor-assisted vehicle from “eco mode” (maximum torque of 3 Nm) to “ride mode” (maximum torque of 20 Nm) as per one embodiment of the present disclosure;
FIG. 12 shows a table illustrating correlation between torque, torque ramp rate and speed over time for a change in operating mode of the motor-assisted vehicle from “eco mode” (maximum torque of 3 Nm) to “ride mode” (maximum torque of 20 Nm) as per another embodiment of the present disclosure;
FIG. 13 shows a table illustrating correlation between torque, torque ramp rate and speed over time for a 0° gradient WOT run of the motor-assisted vehicle as per an embodiment of the present disclosure; and
FIG. 14 shows a table illustrating correlation between torque, torque ramp rate and speed over time for a 0° gradient WOT run of the motor-assisted vehicle as per an embodiment of the present disclosure.
Detailed Description
Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.
The following discussion provides many example embodiments of the inventive subject matter. Although each embodiment represents a single combination of inventive elements, the inventive subject matter is considered to include all possible combinations of the disclosed elements. Thus, if one embodiment comprises elements A, B, and C, and a second embodiment comprises elements B and D, then the inventive subject matter is also considered to include other remaining combinations of A, B, C, or D, even if not explicitly disclosed.
The present invention generally relates to automobiles and more particularly to a system and method for managing torque in motor-assisted vehicles.
All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
In some embodiments, the numbers expressing quantities of ingredients, properties such as concentration, reaction conditions, and so forth, used to describe and claim certain embodiments of the invention are to be understood as being modified in some instances by the term “about.” Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values presented in some embodiments of the invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.
Referring to FIG. 1, there is shown a schematic view of a system 100 to manage torque in a motor-assisted vehicle 110 according to an embodiment of the present disclosure. The system 100 enables to manage the torque by limiting a rate of change of torque. The system 100 accomplishes such limiting of the rate of change of torque by employing, for example, an adaptive torque ramp rate algorithm (discussed in detail herein later). The adaptive torque ramp rate algorithm enables to provide a smoother acceleration to the motor-assisted vehicle 110 without compromising a gradeability or peak load-carrying capacity of the motor-assisted vehicle 110. The torque ramp rate is controlled adaptively or dynamically with respect to the actual torque provided to the motor of the motor-assisted vehicle 110. Consequently, the system 100 enables to reduce jerks experienced by a driver of the motor-assisted vehicle 110 while providing throttle to the motor-assisted vehicle 110 (and for example, while starting the motor-assisted vehicle 110 from standstill). Further, the system 100 enables to provide smoother acceleration to the driver of the motor-assisted vehicle 110 compared to conventional motor-assisted vehicles, thereby, enhancing a user experience for the driver of the motor-assisted vehicle 110. Moreover, the system 100 enables to provide higher operating performance (such as, higher efficiency of a battery and motor) of the motor-assisted vehicle 110, improved thermal management of electronic components (such as, of the battery and motor) of the motor-assisted vehicle 110 as well as increased operating range of the motor-assisted vehicle 110 compared to conventional motor-assisted vehicles. Additionally, in motor-assisted vehicles 110 capable of operating in different driving modes, for example, an electric vehicle capable of operating in a low torque mode (or “eco mode”), an intermediate torque mode (or “ride mode”) and a high torque mode (or “rush mode”), the system 100 enables to provide better usability of the different driving modes in various operating conditions of the motor-assisted vehicle 110.
The system 100 comprises a battery pack 120. The battery pack 120 is adapted to supply operating current to various electronic components of the motor-assisted vehicle 100. For example, the battery pack 120 comprises multiple batteries connected in a series and/or parallel connection, such that each battery comprises multiple cells. In one example, each cell is implemented as a NiMH (nickel-metal-hydride) cell, a NiCd (nickel-cadmium) cell, a Li-ion (lithium-ion) cell or a LiPo (lithium-polymer) cell.
The system 100 also comprises a motor 130. The motor 130 is adapted to generate torque to drive the motor-assisted vehicle 110, for example, by providing the generated torque to wheels of the motor-assisted vehicle 110. Consequently, the motor 130 is operably coupled to the wheels of the motor-assisted vehicle 110 for supplying the torque to the wheels such that the motor-assisted vehicle 110 can be driven on flat surfaces such as roads, incline surfaces such as hills, uneven surfaces such as farmlands and the like. Further, the motor 130 is operably coupled to the battery pack 120. The battery pack 102 is configured to supply operating current to the motor 130 such that the motor 130 converts the operating current to torque to be provided to the wheels of the motor-assisted vehicle 110. In an example, the motor 130 is implemented as a permanent magnet synchronous motor (PMSM). In another example, the motor 130 is implemented as a three-phase alternating current (AC) induction motor.
Moreover, the system 100 comprises a torque estimator 140 adapted to estimate an actual torque generated by the motor 130. The torque estimator 140 can be implemented as a sensor that is operably coupled to the motor 130 and capable of determining an actual torque generated by the motor 130. It will be appreciated that motor-assisted vehicles such as electric vehicles may comprise a motor controller capable of adjusting a torque provided to a motor of the electric vehicle. Such an adjustment may be initiated by a driver of the electric vehicle, for example, by changing a throttle provided to the electric vehicle. However, such a torque demanded by the driver of the electric vehicle may be further varied by the motor controller to provide an adjusted torque to the motor of the electric vehicle such that the adjusted torque corresponds to the actual torque generated by the motor of the electric vehicle. The torque estimator 140 is implemented to estimate such an actual torque (denoted by ΤE hereinafter) generated by the motor 130 of the motor-assisted vehicle 110. In one example, the torque estimator 140 is configured to estimate the ΤE generated by the motor 130 at particular time intervals, such as, after every 10 microseconds. In another example, the torque estimator 140 is configured to estimate the ΤE generated by the motor 130 upon determination of a change in a driving parameter of the motor-assisted vehicle 110.
Further, the system 100 comprises an input unit 150 adapted to receive a driving parameter associated with the motor-assisted vehicle 110. The input unit 150 can be implemented as a hardware element (for example, a touchscreen unit operably coupled to a microprocessor, such that the touchscreen unit is configured to receive inputs from the driver of the motor-assisted vehicle 110), a software element (for example, a software application) or preferably, a combination of hardware and software elements (for example, a software application installed on a carputer operating system associated with the motor-assisted vehicle 110). The input unit 150 can be configured to receive one or multiple driving parameters associated with the motor-assisted vehicle 110. In one example, the input unit 150 is configured to receive driving parameters after specific time intervals, such as, after each 5 microseconds. Alternatively or additionally, the input unit 150 can be implemented using sensors that are capable of determining the driving parameters associated with motor-assisted vehicle 110 during operation of the motor-assisted vehicle 110.
In one embodiment, the driving parameter is selected from a driving mode, a change in throttle position, a load applied on the motor-assisted vehicle 110, an operating parameter associated with the battery pack 120 and a road gradient. For example, the motor-assisted vehicle 110 may be capable of operating in various driving modes associated with different torques provided to the motor 130 of the motor-assisted vehicle 110. As mentioned herein before, the motor-assisted vehicle 110 may have a low torque mode (or “eco mode”), an intermediate torque mode (or “ride mode”) and a high torque mode (or “rush mode”). Consequently, the driver of the motor-assisted vehicle 110 may change the driving mode of the motor-assisted vehicle 110 by, for example, tapping a button on a graphical user interface associated with the carputer of the motor-assisted vehicle 110 or by pressing a physical button provided on a dashboard of the motor-assisted vehicle 110. In another example, the driver of the motor-assisted vehicle 110 may change a throttle position from, for example, 35% to 40% throttle to increase a driving speed of the motor-assisted vehicle 110. In yet another example, one or more co-passengers of the driver of the motor-assisted vehicle 110 may disembark from the motor-assisted vehicle 110, thereby, changing a load applied on the motor-assisted vehicle 110 during its onward journey. In still another example, the motor-assisted vehicle 110 may be driven on an upwards inclination (such as, on a hilly road), thereby, changing the road gradient.
In another example, the operating parameter associated with the battery pack 120 may change during operation of the motor-assisted vehicle 110. As per one embodiment, the battery pack 120 comprises multiple cells and the operating parameter associated with the battery pack is selected from a state of charge (SoC) of the battery pack 120, a state of health (SoH) of the battery pack 120, a temperature of the battery pack 120, a current associated with the battery pack 120, a voltage associated with the battery pack 120, a current associated with each cell of the battery pack 120 and a voltage associated with each cell of the battery pack 120. It will be appreciated that once a charger of the motor-assisted vehicle 110 (for example, an electric vehicle) is disconnected and the motor-assisted vehicle is operated for driving, the SoC of the battery pack 120 of the motor-assisted vehicle 110 will gradually decrease with an amount of operation of the motor-assisted vehicle 110. For example, if the motor-assisted vehicle 110 is charged to 100% SoC of the battery pack 120 of the motor-assisted vehicle 110 and the motor-assisted vehicle 110 is driven for a number of hours, the SoC of the motor-assisted vehicle 110 may decrease to 63%. Further, as the motor-assisted vehicle 110 is put to regular use, the SoH of the battery pack 120 will gradually deteriorate, causing faster discharge of the battery pack 120. For example, the battery pack 120 of a new motor-assisted vehicle 110 may be capable of being charged to a maximum charge of 100%. However, after 2 years of regular usage of the motor-assisted vehicle 110, the battery pack 120 of the battery pack 120 of the user motor-assisted vehicle 110 may be capable of being charged to a maximum charge of only 85%. Consequently, an owner of the motor-assisted vehicle 110 may need to replace the battery pack 120 of the motor-assisted vehicle 110. Also, the temperature of the battery pack 120 may be affected by various internal and external conditions, for example, a time duration of constant driving of the motor-assisted vehicle 110, ambient temperature around the motor-assisted vehicle 110 and the like. Moreover, the current and/or the voltage associated with the battery pack 130 may decrease, for example, with decreasing SoC of the battery pack 130 and/or SoH of the battery pack 130. Similarly, when the battery pack 130 comprises multiple cells, as shown, the current and/or the voltage associated with each cell of the battery pack 130 may decrease with decreasing SoC and/or SoH of the battery pack.
Moreover, the system 100 comprises a motor control device 160. The motor control device can be implemented as a hardware component (for example, microprocessors, microcontrollers and the like), a software component (such as, a software application capable of sending signals to the motor 130 of the motor-assisted vehicle 110 for controlling the torque provided to the motor-assisted vehicle 110) or preferably, a combination of hardware and software components (for example, multiple buttons displayed on a graphical user interface of a carputer of the motor-assisted vehicle 110 allowing the driver of the motor-assisted vehicle 110 to change power provided from the battery pack 120 of the motor-assisted vehicle 110 to the motor 130 of the motor-assisted vehicle 110, such as, by changing a throttle position. In another example, the driver of the motor-assisted vehicle 110 may change the driving mode associated with motor-assisted vehicle 110 to cause the motor control device 160 to modify the torque provided to the motor 130 of the motor-assisted vehicle 110.
The motor control device 160 is configured to determine a change in the driving parameter based on the driving parameter received by the input unit 150. The motor control device 160 may be adapted to comparison of two driving parameters received by the input unit 150, such that the two driving parameters are spaced apart by a specific time duration. For example, the input unit 150 receives a driving parameter DP1 at time T1 and a driving parameter DP2 at time T2, such that T2 is higher than T1. In one example, T2 may be 5 microseconds later than T1. The motor control device 160 is configured to determine a difference between DP2 and DP1 to determine the change in the driving parameter ΔDP according to Equation 1 below:
ΔDP = DP2 − DP1 (1)
Thereafter, the motor control device 160 is configured to determine a demanded torque ΤD based on the determined change in the driving parameter ΔDP. It will be appreciated that the change in the driving parameter will require a different amount of torque. For example, if the motor-assisted vehicle 110 is driving up a steep hill at constant speed of 30 km/h and all other driving parameters of the motor-assisted vehicle 110 remain substantially constant, a higher amount of torque will be required to be provided to the motor 130 of the motor-assisted vehicle 110 to enable the motor-assisted vehicle 110 to keep driving up the hill at the constant speed of 30 km/h.
Subsequently, the motor control device 160 is configured to determine a controlled torque ramp rate (denoted by δΤ/δt, where “t” refers to time in seconds) based on the estimated actual torque ΤE and the determined demanded torque ΤD to achieve the demanded torque ΤD. It will be appreciated that in conventional motor-assisted vehicles, an implemented torque ramp rate is usually of a constant value. For example, the implemented torque ramp rate may be 80 Nm/s or 160 Nm/s. It will be appreciated that such a constant value of the torque ramp rate (for example, due to hardware limitations) causes the conventional motor-assisted vehicles to experience an instantaneous increase in torque when starting from standstill, leading to passengers of such vehicles experiencing a sudden jerk (corresponding to instant acceleration from an inert state) that cannot be changed.
Referring to FIG. 2, there is shown a mapping curve 200 associated with the δΤ/δt corresponding to the ΤE as per an embodiment of the present disclosure. The system 100 comprises a memory (not shown) that is configured to store the mapping curve associated with the δΤ/δt corresponding to the ΤE. As shown, the δΤ/δt is implemented such that, for example, the δΤ/δt decreases with an increase in the ΤE to allow the motor-assisted vehicle 110 to carry loads, drive on roads with steep gradients and the like without utilising torque for acceleration of the motor-assisted vehicle 110. For example, the δΤ/δt is maintained to be low at high operating torque of the motor 130. Consequently, the motor 130 of the motor-assisted vehicle 110 is not allowed to quickly reach high ΤE. It will be appreciated that such a low ΤE is possible when a speed of the motor-assisted vehicle 110 is low because a higher torque is available only in low rotational speed of the motor 130. Moreover, the motor-assisted vehicle 110 bypasses operating zones corresponding to low rotational speed and high torque of the motor 130, thereby, allowing the motor-assisted vehicle 110 to achieve improved vehicle efficiency. The Y axis represents the speed (in rpm) and the X axis represents the torque (in Newton Meter). The map elucidates that the motor 130 is more efficient (on a 0-100 scale), when the speed is higher than 3,000 rpm and the torque is lower than 15 NM. As illustrated, present disclosure provides motor control device 160 that determines variable ramp rate δΤ/δt (i.e., increase or decrease torque per unit time) based on various parameters such as drive mode, road condition, current speed, throttle condition, overall load on vehicle 110 and many more, would results in smoother drive experience to user. The graph may also show that the torque ramp rate can become very low at higher torque region.
The adaptive torque ramp rate δΤ/δt provides a smoother acceleration (e.g., form still stand condition to driving condition of vehicle 110 or sudden change in driving mode etc.,) without losing on gradeability or the peak load carrying capacity. The torque ramp rate is controlled adaptively or dynamically with respect to the current torque provided by the motor. The torque ramp can be decreasing with increased torque to allow the vehicle to carry loads, climb gradients without too much load on motor 130. The variable ramp rate would prevent sudden or rapid torque adjustment, in low speed and high torque condition of EV 110. By implementing this adaptive torque ramp rate, the motor control device 130 prevents sudden increase of higher torque when vehicle 110 is driven at low speed. Further, as the graph shows, the vehicle 110 also navigates smoothly low RPM high torque zones and achieves better efficiency.
Referring to FIG. 3, there is shown a graph 300 illustrating mapping curves for each driving mode of multiple driving modes in the motor-assisted vehicle 110 according to an embodiment of the present disclosure. It will be appreciated that conventional motor-assisted vehicles limit operation of a motor of the motor-assisted vehicle to low speed and high torque region (for example, rotational speeds of the motor to approximately 500 rpm and torque to more than or 15 Nm) for driving of the motor-assisted vehicle in low torque modes (such as an “eco mode” of conventional electric vehicles). It will be appreciated such a region is generally a low efficiency region for motor-assisted vehicles and consequently, driver of such motor-assisted vehicles are required to change modes to high torque modes (such as “ride mode” or “rush mode”) to access higher torque, for example, when the motor-assisted vehicles climb a steep hill. However, such a change in the driving mode of the motor-assisted vehicle results in various other changes in operating parameter of motor-assisted vehicle such as throttle response, current limits, system estimations and the like. The implemented mapping curves for each driving mode of multiple driving modes in the motor-assisted vehicle 110 enables to change the δΤ/δt, thereby, providing a different experience to passengers of the motor-assisted vehicle 110 in various modes, for example, a “comfort mode”, a “dynamic mode” and an “economy mode”, allowing the torque provided to the motor 130 to increase as shown in FIG. 2.
In one embodiment, the motor control device 160 utilizes a machine-learning algorithm to determine the ΤD. For example, the motor control device 160 comprises a processor implementing a supervised, a semi-supervised, an unsupervised or a reinforcement algorithm to determine the ΤD. Optionally, the machine-learning algorithm may be implemented on a cloud server. In one example, the machine-learning algorithm can be a supervised algorithm, such as a k-nearest neighbour (kNN) algorithm, a Naïve Bayes algorithm, an algorithm employing decision trees, a linear regression algorithm, a support vector machine (SVM) including others and/or neural networks.
Referring to FIG. 4, there is shown a flowchart illustrating steps of a method 400 for managing torque in a motor-assisted vehicle as per an embodiment of the present disclosure. At a step 410, an actual torque generated by a motor of the motor-assisted vehicle is estimated. At a step 420, a driving parameter associated with the motor-assisted vehicle is received. At a step 430, a change in the driving parameter is determined based on the received driving parameter. At a step 440, a demanded torque is determined based on the determined change in the driving parameter. At a step 450, a controlled torque ramp rate is determined based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
In one embodiment, the driving parameter is selected from a driving mode, a change in throttle position, a load applied on the motor-assisted vehicle, an operating parameter associated with the battery pack and a road gradient.
In another embodiment, the method 400 comprises storing a mapping curve associated with the controlled torque ramp rate corresponding to the actual torque
In yet another example, the method 400 comprises storing a corresponding mapping curve for each driving mode of multiple driving modes in the motor-assisted vehicle.
Referring to FIG. 5, there is shown a block diagram 500 of an exemplary operation of a system (such as the system 100 shown in FIG. 1) according to an embodiment of the present disclosure. As shown, a driver of a motor-assisted vehicle provides a throttle input between 0 to 100% using throttle block 510. Subsequently, the throttle input is converted to ΤD in block 520 using the mapping curve shown in FIG. 3. Thereafter, the ΤD is filtered in block 530. Next, the filtered ΤD is employed as an input to a field oriented control (FOC) of block 540 that generates a corresponding current reference to generate a motor torque corresponding to the ΤD. Then, in block 550, a ΤE is estimated based on the corresponding current reference determined in block 540. In a final step, an δΤ/δt is added to achieve the estimated ΤE in block 550.
In one embodiment, the memory is configured to store values of ΤD. For example, the memory is configured to store the value of ΤD for each time point corresponding to a specified duration, such as, 5 microseconds, 10 microseconds and the like. In one example, let the value of ΤD at time point t1 be ΤD1 and value of ΤD at time point t2 be ΤD2, such that t2 is a time point after t1. In such an example, the motor control device 160 is configured to determine δΤ/δt using the Equation (2) below:
δΤ/δt = "ΤD2-ΤD1" /"t2-t1" (2)
Referring now to FIG. 6, there is shown a block diagram illustrating a motor control device 600 to manage torque in a motor-assisted vehicle as per an embodiment of the present disclosure. The device 600 can be implemented using a hardware unit, a software block or preferably, a software block running on a hardware unit. The device comprises a memory (not shown) configured to store multiple executable instructions and a processor operably coupled to the memory and operable to execute the multiple executable instructions to estimate an actual torque generated by a motor of the motor-assisted vehicle, receive a driving parameter associated with the motor-assisted vehicle, determine a change in the driving parameter based on the received driving parameter, determine a demanded torque based on the determined change in the driving parameter and determine a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
In the FIGs. 7-14 shown below, there are shown torque ramp rate profiles (e.g. ‘Torque Ramp A’ and ‘Torque Ramp B’). The ‘Torque Ramp A’ is associated with a maximum torque ramp rate of 160 Nm/s for the motor-assisted vehicles and the ‘Torque Ramp B’ is associated with a maximum torque ramp rate of 80 Nm/s for the motor-assisted vehicles. It will be appreciated that for motor-assisted vehicles, there can be multiple torque ramp rate profiles that can be used depending on the operating modes and a riding pattern (or behaviour) of the drivers of the motor-assisted vehicles.
Referring to FIG. 7, there is shown a table 700 illustrating correlation between torque, torque ramp rate, speed, and mechanical power over time for a single driver using the motor-assisted vehicle as per an embodiment of the present disclosure. The single driver operates the motor-assisted vehicle as per the first torque ramp rate profile, i.e., ‘Torque Ramp A’ and suddenly gives throttle from 0% to 50%. As shown, as time progresses from 8s to 20s, the torque generated by the motor of the motor-assisted vehicle decreases from 22 Nm to 6 Nm. However, the torque ramp rate as well as the speed of the motor-assisted vehicle increase. It will be appreciated that because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring to FIG. 8, there is shown a table 800 illustrating correlation between torque, torque ramp rate, speed, and mechanical power over time for a single driver using the motor-assisted vehicle as per another embodiment of the present disclosure. The single driver operates the motor-assisted vehicle as per the second torque ramp rate profile, i.e. ‘Torque Ramp B’ and suddenly gives throttle from 0% to 50%. As shown, in comparison with the table 700 of FIG. 7, the increase in torque ramp of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp B’ is slower than that of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’. However, the speed of the motor of the motor assisted vehicle at each time point as well as an increase in speed of the motor are higher than that of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’. Therefore, similarly to the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring now to FIG. 9, there is shown a table 900 illustrating correlation between torque, torque ramp rate, speed, and mechanical power over time for a driver operating using the motor-assisted vehicle with a pillion rider or with additional payload according to an embodiment of the present disclosure. The driver operates the motor-assisted vehicle as per the first torque ramp rate profile, i.e. ‘Torque Ramp A’ and suddenly gives throttle from 0% to 70%. As shown, as time progresses from 8 s to 20 s, the torque supplied to the motor of the motor-assisted vehicle decreases from 22 Nm to 14.5 Nm. However, the torque ramp rate as well as the speed of the motor-assisted vehicle increase. It will be appreciated that because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring to FIG. 10, there is shown a table 1000 illustrating correlation between torque, torque ramp rate, speed, and mechanical power over time for driver operating using the motor-assisted vehicle with a pillion rider or with additional payload according to an embodiment of the present disclosure. The driver operates the motor-assisted vehicle as per the second torque ramp rate profile, i.e., ‘Torque Ramp B’ and suddenly gives throttle from 0% to 70%. As shown, in comparison with the table 900 of FIG. 9, the increase in torque ramp of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp B’ is slower than that of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’. However, the speed of the motor of the motor assisted vehicle at each time point as well as an increase in speed of the motor are higher than that of the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’. Therefore, similarly to the motor-assisted vehicle operating as per the torque ramp rate profile ‘Torque Ramp A’, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring now to FIG. 11, there is shown a table 1100 illustrating correlation between torque, torque ramp rate and speed over time for a change in operating mode of the motor-assisted vehicle from “eco mode” (maximum torque of 3 Nm) to “ride mode” (maximum torque of 20 Nm) as per one embodiment of the present disclosure. The driver operates the motor-assisted vehicle as per the first torque ramp rate profile, i.e., ‘Torque Ramp A’. As shown, as time progresses from 8s to 20s, the torque supplied to the motor of the motor-assisted vehicle decreases from 19 Nm to 14 Nm with an increase in the torque ramp rate from 22 Nm/s to 60 Nm/s. The motor of motor-assisted vehicle correspondingly operates at higher speeds starting from 500 rpm and going up to 4000 rpm at 20s. It will be appreciated that because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring now to FIG. 12, there is shown a table 1200 illustrating correlation between torque, torque ramp rate and speed over time for a change in operating mode of the motor-assisted vehicle from “eco mode” (maximum torque of 3 Nm) to “ride mode” (maximum torque of 20 Nm) as per another embodiment of the present disclosure. The driver operates the motor-assisted vehicle as per the second torque ramp rate profile, i.e. ‘Torque Ramp B’. As shown, in comparison with the table 1100 of FIG. 11, as time progresses from 8 s to 20 s, the torque supplied to the motor of the motor-assisted vehicle similarly decreases from 19 Nm to 14 Nm but with a slower increase in the torque ramp rate from 20 Nm/s to 30 Nm/s. Consequently, the motor of motor-assisted vehicle operates at comparatively higher speeds starting from 700 rpm and going up to 4000 rpm at 20 s. However, similarly to FIG. 11, as the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thus, providing a smoother riding experience to the driver.
Referring to FIG. 13, there is shown a table 1300 illustrating correlation between torque, torque ramp rate and speed over time for a 0° gradient wide-open throttle (WOT) run of the motor-assisted vehicle as per an embodiment of the present disclosure. The driver of the motor-assisted vehicle suddenly gives the throttle to 100%. The ramp rate remains invariable at 160 Nm/s. However, the torque decreases from 16 Nm to 12 Nm and correspondingly, the speed of the motor increases from 0 rpm to 5000 rpm. Consequently, because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thus, providing a smoother riding experience to the driver.
In another embodiment, for a 10° gradient WOT run of the motor-assisted vehicle, when the driver of the motor-assisted vehicle suddenly gives the throttle to 100%, the ramp rate remains invariable at 160 Nm/s. Similarly, the torque remains stable at 22.5 Nm before decreasing and correspondingly, the speed of the motor increases from 1000 rpm to 6500 rpm. Thus, because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
Referring to FIG. 14, there is shown a table 1400 illustrating correlation between torque, torque ramp rate and speed over time for a 0° gradient WOT run of the motor-assisted vehicle as per an embodiment of the present disclosure. The driver of the motor-assisted vehicle suddenly gives the throttle to 100%. As shown, the ramp rate increases from 35 Nm/s to 65 Nm/s as the torque decreases from 16 Nm to 12 Nm. The speed of the motor increases from 0 rpm to 5000 rpm. Further, as the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
In another embodiment, for a 10° gradient WOT run of the motor-assisted vehicle, when the driver of the motor-assisted vehicle suddenly gives the throttle to 100%, the ramp rate increases from 0 Nm/s to 160 Nm/s as the torque decreases from 25 Nm to 0 Nm. However, the speed of the motor increases from 1000 rpm to 6500 rpm. Therefore, because the speed of the motor-assisted vehicle increases with the decrease in the torque supplied to the motor of the motor-assisted vehicle, an inefficient region associated with low speed and high torque is avoided, thereby, providing a smoother riding experience to the driver.
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 preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C … and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.

Advantages of the Invention
An advantage offered by the present invention is that the disclosed system and method enable to efficiently and reliably manage torque provided to motors in motor-assisted vehicles.
Another advantage offered by the present invention is that torque demands are adaptively varied to reduce electrical charge consumption in motor-assisted vehicles.
Yet another object of the present invention is that a comparatively lower torque is utilised in each operating mode of motor-assisted vehicles, thereby, increasing a range of operation of the motor-assisted vehicles.
Still another object of the present invention is that batteries and motors of the motor-assisted vehicles are subjected to comparatively lower fatigue and stress, thus, improving a performance of the motor-assisted vehicles. , Claims:I/we claim:
1. A system to manage torque in a motor-assisted vehicle, the system comprising:
a battery pack;
a motor;
a torque estimator adapted to estimate an actual torque generated by the motor;
an input unit adapted to receive a driving parameter associated with the motor-assisted vehicle;
a motor control device configured to:
determine a change in the driving parameter based on the driving parameter received by the input unit;
determine a demanded torque based on the determined change in the driving parameter; and
determine a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
2. The system as claimed in claim 1, wherein the driving parameter is selected from:
a driving mode;
a change in throttle position;
a load applied on the motor-assisted vehicle;
an operating parameter associated with the battery pack; and
a road gradient.
3. The system as claimed in claim 2, wherein the battery pack comprises multiple cells and the operating parameter associated with the battery pack is selected from:
a state of charge (SoC) of the battery pack;
a state of health (SoH) of the battery pack;
a temperature of the battery pack;
a current associated with the battery pack;
a voltage associated with the battery pack;
a current associated with each cell of the battery pack; and
a voltage associated with each cell of the battery pack.
4. The system as claimed in claim 1, wherein the motor control device comprises a memory configured to store a mapping curve associated with the controlled torque ramp rate corresponding to the actual torque.
5. The system as claimed in claim 4, wherein the memory is configured to store a corresponding mapping curve for each driving mode of multiple driving modes in the motor-assisted vehicle.
6. The system as claimed in claim 1, wherein the motor control device utilizes a machine-learning algorithm to determine the demanded torque.
7. A method for managing torque in a motor-assisted vehicle, the method comprising:
estimating an actual torque generated by a motor of the motor-assisted vehicle;
receiving a driving parameter associated with the motor-assisted vehicle;
determining a change in the driving parameter based on the received driving parameter;
determining a demanded torque based on the determined change in the driving parameter; and
determining a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.
8. The method as claimed in claim 7, wherein the driving parameter is selected from:
a driving mode;
a change in throttle position;
a load applied on the motor-assisted vehicle;
an operating parameter associated with the battery pack; and
a road gradient.
9. The method as claimed in claim 7, wherein the method comprises storing a mapping curve associated with the controlled torque ramp rate corresponding to the actual torque.
10. The method as claimed in claim 9, wherein the method comprises storing a corresponding mapping curve for each driving mode of multiple driving modes in the motor-assisted vehicle.
11. A motor control device to manage torque in a motor-assisted vehicle, the device comprising:
a memory configured to store multiple executable instructions; and
a processor operably coupled to the memory and operable to execute the multiple executable instructions to:
estimate an actual torque generated by a motor of the motor-assisted vehicle;
receive a driving parameter associated with the motor-assisted vehicle;
determine a change in the driving parameter based on the received driving parameter;
determine a demanded torque based on the determined change in the driving parameter; and
determine a controlled torque ramp rate based on the estimated actual torque and the determined demanded torque to achieve the demanded torque.