Description:FORM 2

THE PATENTS ACT, 1970 (39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
METHOD AND SYSTEM FOR MODULATING ELECTRIC CURRENT FOR ELECTRIC VEHICLES

Applicant:
River Mobility Private Limited
A company based in India,
having address as:
No. 25/3, KIADB EPIP Zone, Seetharampalya, Hoodi Road, Mahadevapura, Whitefield, Bengaluru - 560048

The following specification describes the invention and the manner in which it is to be performed.
PRIORITY INFORMATION
The present application does not claim a priority from any other application.
TECHNICAL FIELD
The present subject matter described herein, relates to the improvement of efficiency and the extension of the operating range of electric vehicles. Particularly, the present subject matter relates to a method and system for modulating electric current for electric vehicles for increasing the efficiency of electric vehicles.
BACKGROUND
With rapid adoption of electric vehicles, a significant amount of research and development is being conducted to increase the efficiency and operational range of electric vehicles. One of the methods to improve the efficiency of electric vehicles is through controlling the amount of current discharged by the battery that powers the electric motor of an electric vehicle. However, conventional methods of controlling electric charge input to the motor do not consider certain operating conditions of the vehicle. For example, when the vehicle is under heavy load condition or climbing up steep gradients the torque required to overcome such conditions is higher than normal operating conditions. Therefore, an optimum solution is required that can dynamically provide output power based on the vehicle operating conditions.
SUMMARY
Before the present system(s) and method(s) are described, it is to be understood that this application is not limited to the particular system(s), and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosures. It is also to be understood that the terminology used in the description is for the purpose of describing the particular implementations or versions or embodiments only and is not intended to limit the scope of the present application. This summary is provided to introduce aspects related to a system and a method for controlling discharge of an electric current in a Battery Driven Vehicle (BDV). This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
In one implementation, a method for controlling or modulating the discharge of an electric current in a Battery Driven Vehicle (BDV) is disclosed. The method may involve monitoring a real time speed of the vehicle and determining a real time instantaneous acceleration of the vehicle using the monitored speed of the vehicle. Additionally, the method may determine a State of Charge (SoC) of a battery powering the vehicle. The method may dynamically control an amount of electric current discharged from the battery based on the instantaneous acceleration of the vehicle. Further, the maximum amount of electric current that can be discharged from the battery at any point in time may be determined based on the determined State of Charge (SoC) of the battery.
In one implementation, a system for controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV) is disclosed. The system may include a memory and a processor coupled to the memory. The memory may store multiple instructions to be executed by the processor for controlling discharge of electric current of the battery. The processor may monitor a speed of the vehicle in real time and an instantaneous acceleration of the vehicle may be determined in real time using the monitored speed of the vehicle. Further, the processor may determine a State of Charge (SoC) of a battery powering the vehicle. The processor may dynamically control an amount of electric current discharged from the battery based on the instantaneous acceleration of the vehicle. Further, the maximum amount of electric current discharged from the battery may be determined based on the State of Charge (SoC) of the battery.
In another implementation, a system for controlling or modulating a discharge of an electric current in a Battery Driven Vehicle (BDV) is disclosed. The system may include a first control unit for monitoring a speed of the vehicle in real time. A second control unit may be utilized for determining an instantaneous acceleration of the vehicle in real time using the monitored speed of the vehicle. Also, a third control unit may be configured for determining a State of Charge (SoC) of the battery powering the vehicle. Subsequently, the second control unit may dynamically control an amount of electric current discharged from the battery based on the determined instantaneous acceleration of the vehicle. Further, a maximum amount of electric current that can be discharged from the battery at any given point in time may be determined based on the State of Charge (SoC) of the battery.
In one aspect, the aforementioned method for controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV) may be performed by a processor with multiple processing cores using programmed instructions stored in a memory.
BRIEF DESCRIPTION OF THE DRAWINGS
The foregoing detailed description of embodiments is better understood when read in conjunction with the appended drawings. For the purpose of illustrating of the present subject matter, an example of a construction of the present subject matter is provided as figures, however, the invention is not limited to the specific method and system for controlling discharge of an electric current in a Battery Driven Vehicle (BDV) disclosed in the document and the figures.
The present subject matter is described in detail with reference to the accompanying figures. In the figures, the leftmost digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to refer to various features of the present subject matter.
Figure 1 illustrates a method for controlling a discharge of an electric current in accordance with an embodiment of the present subject matter.
Figures 2, 3 and 4 illustrate variation of State of Charge (SoC) based current limits in different ride modes of the vehicle.
Figure 5 illustrates an example implementation of a system for modulating electric current for electric vehicles with an embodiment of the present subject matter.
Figure 6a illustrates an example implementation of a Motor Control Unit (MCU), its components and modulation of electric current for electric vehicles in a Vehicle Control Unit (VCU).
Figure 6b illustrates an example implementation of a Motor Control Unit (MCU), its components and a Vehicle Control Unit (VCU) in a single processor system.
Figure 7 illustrates an example PID controller for calculating an acceleration based current duration with an embodiment of the present subject matter.
Figure 8 illustrates an example of an artificial neural network, in accordance with an embodiment of the present subject matter.
The figure depicts an embodiment of the present disclosure for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.

DETAILED DESCRIPTION
Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words "monitoring," “controlling”, modulating, "determining," "dynamically," "instantaneous," and other forms thereof, are intended to 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. 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 system and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary system and methods are now described.
The disclosed embodiments are merely examples of the disclosure, which may be embodied in various forms. Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments described but is to be accorded the widest scope consistent with the principles and features described herein.
The present subject matter discloses a method and a system for dynamically controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV). Some of the known current modulation or control algorithms limit the maximum torque output of the electric motor through hard coded values. Also, in these current control techniques or algorithms, the dynamic control of the battery discharge current is achieved based on external requests from the vehicle. Typically, a battery discharge current reduction ensures limited torque output from the motor. While limiting a maximum torque, power consumption is also limited, however torque cannot be limited to the point where the vehicle becomes non-driveable under certain conditions. Therefore, a dynamic control of discharge of battery current would be required for efficient vehicle operation.
The dynamic control of discharge of battery current may depend on instantaneous acceleration of the vehicle. The Battery Driven Vehicle may include a pure electric vehicle that is powered completely by batteries, or it may also include a hybrid electric vehicle. A hybrid vehicle generates power through an internal combustion engine and operates through electric motors driven by the battery. Further, a maximum current that can be discharged from the battery may be limited by factors such as a State of Charge (SoC) of the battery and a ride mode of the vehicle.
Additionally, the method and system also determine an acceleration based current limit and a State of Charge (SoC) based current limit. A combined current limit is calculated using the acceleration based current limit and State of Charge (SoC) based current limit. The combined current limit indicates a peak current limit that may be drawn by a Motor Control Unit (MCU) to drive the motor. Further, the peak current limit determines a maximum torque delivered by the motor during operation.

Referring now to Figure 1, a method 100 for controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV) is shown in accordance with an embodiment of the present subject matter. The method 100 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, etc., that perform particular functions or implement particular abstract data types.
The method 100 for controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV) may be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below, the method 100 may be considered to be implemented in the system 500 of Figure 5.
Referring back to Figure 1, a method for controlling or modulating an electric current for electric vehicles for an electric vehicle is disclosed. A method 100 for controlling discharge of an electric current in a Battery Driven Vehicle (BDV) is disclosed. Firstly, at step 101, the speed of the vehicle is monitored in real time. The vehicle speed value is calculated by a Motor Control Unit (MCU) or an actuator using the rotational speed sensor output value. Some exemplary rotational speed sensors known in the art include but are not limited to Hall effect sensors, magneto resistive sensors, etc. that can be mounted on the electric motor of the vehicle. The rotational speed sensor would sense the revolutions per minute (RPM) of the motor of a motorcycle and the sensed RPM value is converted into the vehicle speed as shown below:
For a motorcycle or an e-bike without gear: Speed =Motor RPM÷8.2
For a motorcycle or a e-bike with gear: Speed=Motor RPM÷ (Gear ratio of the selected gear). In the motorcycle or e-bike with a gearbox, vehicle speed is equal to motor RPM divided by the gear ratio w.r.t the gear in which the driver is driving the motorcycle.
At step 102, the Motor Control Unit determines an instantaneous acceleration of the vehicle in real time using the calculated vehicle speed.
Subsequently, at step 103, a State of Charge (SoC) of the battery is determined. A State of Charge (SoC) for a battery is defined as the level of charge remaining relative to its full charge capacity. A battery may include one or more cells to convert chemical energy into electrical energy. Mathematically, the SoC of the battery is defined as the ratio between the amount of charge extractable from one or more cells at a specific point of time and the total capacity of the battery. A Battery Management System (BMS) determines the State of Charge (SoC) of the battery. As the state of charge of the battery drops, the current needed from the battery to achieve the same vehicle acceleration increases. Therefore, when the rate of change of the vehicle's acceleration is limited, a Motor Control Unit (MCU) would draw less peak current. Due to less peak current drawn a lower torque would be produced by the motor and, in turn, the amount of energy needed from the battery pack will also get reduced.
Hence, at step 104, a battery discharge current is controlled based on the instantaneous acceleration of the vehicle. Alternatively, an acceleration-based current deration is achieved i.e., current discharged from the battery pack is reduced by reducing the torque till the acceleration reaches a set limit. An acceleration-based current deration may be achieved through a PID (Proportional, Integral, Derivative Controller) controller to limit the current. A Vehicle Control Unit (VCU) determines the vehicle acceleration and the acceleration based current limit.
Subsequently, at step 105, a maximum current that can be discharged from the battery may be limited based on multiple factors such as State of Charge (SoC) of the battery and ride mode of the vehicle. In one embodiment, a State of Charge (SoC) and existing ride mode of the vehicle would decide the maximum current discharged from the battery pack. For example, a State of Charge (SoC) of the battery at any point of time would set the peak current limit that can be discharged from the battery pack. Further, a ride mode of the vehicle would determine the maximum acceleration that the vehicle could achieve. The maximum acceleration limit reduces the current discharged from the battery pack by reducing the torque until a point when the acceleration of the vehicle reaches the set peak current limit based on the existing SOC of the battery. The State of Charge (SoC) based current deration and the acceleration-based current deration in conjunction limits the current discharged from the battery pack and hence the torque that the motor generates. A Battery Management System (BMS) of the vehicle determines a SOC of the battery and a Vehicle Control Unit (VCU) determines the SOC based current limit. The VCU also determines acceleration based current limit. The acceleration-based current deration may operate based on the existing ride mode of the vehicle as determined by the VCU.
The ride mode of the vehicle may be selected from a plurality of ride modes available such as, sports mode, city mode, eco mode, track mode or any other modes that may be available on the vehicle. In general, the basic principle behind providing various ride modes on the vehicle is to control the vehicle’s performance based on available power for use and controlling throttle response. A throttle response indicates how quickly the motor responds to a rider’s throttle inputs. Therefore, depending on the ride mode of the vehicle, the driving experience of the rider changes and the range covered by the vehicle. A ride mode of the vehicle may be selected by a rider while riding the vehicle. In an alternate embodiment, a vehicle can automatically select the best ride mode for the vehicle based on the certain conditions such as, current road conditions, battery state of charge (SOC), environmental conditions, and/or riding history of the vehicle rider. In an alternate embodiment, multiple user profiles may be automatically saved on the vehicle locally and a particular rider profile may be activated based on the current rider of the vehicle. In another embodiment, the user profile data may be saved on a cloud, or a server and the vehicle may access the user related data via an internet connectivity. The vehicle may connect to the cloud or a server via the internet using an onboard telematics unit. The internet connectivity to the vehicle may also be provided by Wi-Fi connections or wireless hotspots. A wireless hotspot may be accessed from other devices such as through smartphone pairing or may be available in common public access areas such as common utility areas, charging zones, other traffic/road infrastructure etc.
A user profile may be created and/or updated using demographic data collected from the user, vehicle driving history, vehicle settings, navigation routes, location information captured through GPS or any other location determination systems such as through cell towers or Wi-Fi Systems etc. In one implementation, the vehicle may connect to the cloud or server through a wireless communication network such as cellular or a Wi-Fi connection. The communication network may use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, for communication between vehicle and cloud or server. Further the network may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, user devices and the like.
Referring back to step 105, a processor or the Vehicle Control Unit (VCU) after obtaining relevant information related to ride mode of the vehicle and SOC of the battery pack starts controlling the discharge current from the battery pack. The method for controlling the discharge current for electric vehicles of present subject matter is based on the instantaneous acceleration of the vehicle. The amount of torque required from the motor is determined based on the acceleration required to cover a particular distance by twisting the throttle by a rider of the vehicle. A Motor Control Unit (MCU) determines the required amount of torque and controls the amount of electric current that is discharged from the battery to the motor in order to generate the required torque for the required acceleration. This process results in discharge of battery current and electrical energy from the battery pack. The battery pack provides a set amount of electrical energy based on the battery design and specifications of the battery pack. The electric current discharged from the battery pack increases for the same acceleration as the state of charge of the battery increases. Therefore, reducing the peak current drawn by the Motor Control Unit (MCU) limits the rate of change of acceleration and hence the torque generated by the motor. The reduction in the torque delivered ensures the power discharged from the battery is also reduced, in other words current discharged from the battery is limited.
In one embodiment, the total amount of electric current discharged from the battery is controlled via the Vehicle Control Unit (VCU). The Vehicle Control Unit (VCU) provides instructions to the Motor Control Unit (MCU) to draw the specific amount of electric current required to deliver the required torque. A maximum value of acceleration is applied to a measured value of motor speed by the Motor Control Unit (MCU). The maximum acceleration value of the vehicle may depend on the existing ride mode of the vehicle. A maximum acceleration value ensures a maximum amount of current that would be drawn by the Motor Control Unit (MCU) and hence the torque generated by the motor. The limited torque generated by the motor ensures reduction in the energy consumed from the battery pack. This limited maximum current may be called an acceleration based current limit. In one embodiment an acceleration based current limit is determined based on the maximum acceleration as determined by a current ride mode of the vehicle.
Similarly, a State of Charge (SoC) based current limit is determined by a Battery Management System (BMS). The SoC based current limit would have different peak current values or current limits based on the SoC available at a given instance.
In another embodiment, a total deration current limit or a combined peak current is calculated based on the acceleration based limit and the SoC based current limit. As shown below:
Deration_Current_Limit = SOC_Current_Limit_A - Acceleration_Current_Limit_A
(Equation 1)
In one of the embodiments, the method for modulating or controlling electric current for electric vehicles may be implemented on a Vehicle Control Unit (VCU). Different ride modes of the vehicle are defined in the VCU, and each ride mode would have a corresponding set current limit that can be discharged from the battery pack. As the State of Charge (SoC) of the battery pack decreases, the maximum available current also decreases as a result the acceleration for the vehicle also reduces. Figures 2, 3 and 4 show the State of Charge (SoC) based current limits in different ride modes of the vehicle. As the State of Charge (SoC) drops, the peak current available also drops based on the ride mode selected. As shown in Figure 2, when the vehicle is in Ride mode 1, the peak current limit drops from 83% of the peak value to around 40% of the peak value at 50% State of Charge (SoC) and remains constant till 10% State of Charge (SoC). In Figure 3, when the vehicle is in Ride mode 2, the peak current limit drops from 100% of peak current value close to 60% of peak current value at 50% State of Charge (SoC) and remains constant till 10% State of Charge (SoC). In Figure 4, when the vehicle is in Ride mode 2, the peak current limit is constant from 100 % state of charge to 50 % state of charge and the current drops to around 80% of peak value at 30% State of Charge (SoC). Hence, the State of Charge (SoC) based current deration in conjunction with acceleration based deration, limits the current drawn by the motor and subsequently the torque delivered. In other words, the current modulation or control technique limits the torque delivered by the electric motor by derating the battery discharge current based on the acceleration of the vehicle and the State of Charge (SoC) of the battery. The State of Charge (SoC) based current deration sets the peak current limit that can be discharged from a battery pack. The acceleration-based current deration reduces the current discharged from the battery pack by reducing the torque till the acceleration reaches the corresponding current limit set by SOC based deration.
Referring to Figure 5, a system for modulating or controlling discharge of the electric current of the vehicle is disclosed. The system may be implemented inside a vehicle subsystem such as a Vehicle Control Unit (VCU). The system may interact with other vehicle subsystems via a combination of physical and digital signals as indicated in Figure 5. The system 500, determines a combined current limit using the State of Charge (SoC) based current limit and a vehicle ride mode based current limit. A maximum current limit is calculated based on the current limits obtained from State of Charge (SoC) of the battery and existing vehicle ride mode. In one of the embodiments, a ride mode of the vehicle may be automatically selected by a processor on a vehicular subsystem. Alternatively, a Vehicle Control Unit (VCU) may also select the ride mode of the vehicle. In another embodiment, a rider of the vehicle may also select the ride mode of the vehicle.
A motor control ECU or Motor Control Unit (MCU) 501 provides motor speed 504 to the acceleration limiter 507 to calculate an acceleration based current limit. The acceleration limiter 507 also obtains the existing vehicle drive or ride mode 505 from a vehicle control ECU or Vehicle Control Unit (VCU) 502 and hence a maximum acceleration set point for acceleration is obtained. Similarly, a Battery Management System 503 provides an existing State of Charge (SoC) 506 of the battery pack to the SOC limiter 509. The output of the SOC limiter 509 is the SOC based peak current limit.
Subsequently, a motor current limiter 508 outputs a dynamic discharge current limit based on the current limits set by acceleration limiter 507 and SOC limiter 509. Furthermore, the output from the motor control limiter 508 is fed to the protection limits 510 module to saturate the output current to a maximum and a minimum value. The maximum value is determined by the battery operational limits and minimum value is determined by the minimum drivable current required. Finally, the discharge current is provided to the motor control ECU or Motor Control Unit (MCU) 511. This limited current results in limiting the torque delivered by the motor to the vehicle.
Referring to Figure 6a, a system implementation with a Motor Control Unit (MCU) and its components along with Vehicle Control Unit (VCU) is disclosed. The system 600 indicates an example implementation of a current modulation or control technique for an electric vehicle when a throttle input and ride mode is received by the rider of the vehicle. In one embodiment, the current modulation is achieved by derating the amount of current discharged by the battery pack. The system utilizes inputs like a throttle input and a ride mode of the vehicle for controlling discharge of an electric current in a Battery Driven Vehicle (BDV). A current control or modulation system 600 may be implemented with all its encompassing functions to reduce the power consumption of the vehicle through actively controlling the current limits supplied to the motor 605. The system 600 involves multiple hardware and software components as shown in Figure 6a. A motor control ECU or Motor Control Unit (MCU) 609 monitors the motor speed 606 of the vehicle in real time. The measured/monitored motor speed 606 value is fed to a Vehicle Control Unit (VCU) 608 via a CAN bus. The motor speed 606 is subsequently utilized by the VCU 608 to calculate the instantaneous acceleration in the real time according to equation 5 as disclosed in the present subject matter. The in-vehicle communication between multitude of electronic control units (ECU) such as VCU, MCU and BMS subsystems occurs via a controller-area network (CAN) bus. The controller-area network (CAN or CAN-bus) is a multi-master broadcast serial bus standard for interconnecting electronic control devices. The CAN-bus is a vehicle bus standard designed to allow microcontrollers and devices to interact with each other within a vehicle without the need for a host computer. The CAN-bus is also used to connect the engine control unit, cruise control, audio systems, windows, doors, seat control etc. in automobiles. The communication signal carried by the CAN bus between VCU 608 and MCU 609 may be a combination of physical and digital signals. For example, vehicle throttle input, 601, motor torque limit 605 and motor speed signal 606 are physical signals. The current demand, current limiter and VCU 608 output indicating a current limit signal are digital signals.
Referring back to Figure 6a, a Motor Control Unit (MCU) 609 in conjunction with VCU 608 and a BMS (not shown in the figure) controls the discharge current of the vehicle. Below mentioned are the different steps performed by a Motor Control Unit (MCU) 609 or the actuator:
A required amount of torque is determined based on the applied throttle input 601.
The throttle input 601 is converted into a corresponding torque demand 602.
The torque demand 602 is converted into a corresponding current demand 603.
The Motor Control Unit 609 receives a current limit value 610 at current limiter module 603. The current limit value 610 is obtained through a deration logic or a deration method implemented inside the Vehicle Control Unit (VCU) 608.
The motor recalculates the limited torque value 604 based on the current limiter output 611. The current limiter 611 provides a current limit value based on the current value obtained from the Vehicle Control Unit (VCU) 608 and current demand 603 based on throttle input 601. The limited current value subsequently limits the torque delivered by the motor.
A limited torque value 604 is then delivered to the vehicle drivetrain by the motor 605.
The vehicle or motor speed 606 is measured by the Motor Control Unit (MCU) 609 is sent back to the Vehicle Control Unit (VCU) 608.
As shown in Figure 6a, a Vehicle Control Unit (VCU) 608 implements the current modulation or control algorithm 607. In one embodiment, the current modulation or control is achieved by derating the amount of current discharged by the battery pack. Below mentioned are the different steps performed by the VCU 608:
The motor speed value 606 sent from the Motor Control Unit (MCU) 609 via the CAN bus is used to determine the real time vehicle acceleration.
A maximum vehicle acceleration is applied to the observed vehicle speed obtained from the MCU 609.
The maximum acceleration allowed is based on the drive mode or ride mode of the vehicle. For example, a vehicle mode can be selected from - ride mode, sport mode, rush mode, track mode, eco mode etc.
The maximum acceleration is utilized to calculate an acceleration based current limit as shown in Figure 5, by acceleration limiter 507.
Simultaneously, a State of Charge (SoC) value 506 as shown in figure 5 is received from a Battery Management System (BMS) 503 that is used to determine an SoC based current limit by the SoC limiter 509.
The acceleration based current limit as provided by an acceleration limiter 507 and an SOC based current limit as provided by the SOC limiter 509 is utilized to calculate a combined current limit. The combined current limit is provided by a motor current limiter 508 which is fed to the Motor Control Unit (MCU) 511. The combined current limit indicates a peak current that can be drawn by the MCU 511.
The peak current controls the maximum torque delivered by the motor to the wheels thereby limiting acceleration.
Under heavy loads or climbing steep gradients, the wheel acceleration observed is lesser for the same torque and hence higher amounts current and therefore higher amount of torque is allowed to be delivered by the Motor Control Unit (MCU) 609.
When on flat road conditions or under lesser load, the wheel accelerations observed for the same value of torque supplied is higher, hence the VCU 608 limits the current to reduce the current supplied by the MCU 609 to the motor 605.
A combined current limit for the electric current deration as discussed in the VCU functionalities of Figure 6a could be obtained by determining a SOC based current limit and an acceleration based current limit. A Battery Management System (BMS) is used to determine the State of Charge (SoC) of the battery pack. The SOC value obtained by the BMS is used to calculate the SOC based current limit. In one of the embodiments, the SoC may be monitored in real-time. Alternatively, the SoC may be monitored at a frequency of every 1 sec or 1 millisec. In another embodiment, the SoC frequency at which the battery SoC is monitored may be configured by the system. The maximum current limit that can be discharged from a battery varies as per the SoC value for a given instance as shown in exemplary cases in Figure 2, Figure 3 and Figure 4. Similarly, an acceleration based current limit may be obtained based on the maximum acceleration allowed to the vehicle. The maximum acceleration at a given instance may be obtained based on the current vehicle ride mode. Subsequently, a combined current limit or deration current limit is calculated according to the equation 1 disclosed in the present subject matter. The acceleration based current limit may be obtained through a PID (Proportional, Integral, Derivative) controller.
Referring to Figure 7, shows a Proportional, Integral, Derivative (PID) control system 700 in action according to an embodiment of the subject matter disclosed. The acceleration based deration may use a PID (Proportional, Integral, Derivative) controller to limit the electric current. The PID control system is a close loop control system which has feedback signal ‘motor acceleration’ 703. The PID control system compares a process variable via a feedback signal 703 with set point 701 ‘motor acceleration’.As a result of the comparison an error signal 702 is generated and according to the error signal 702 the controller adjusts the output 709 of the system. This process is carried on until the error becomes zero or process variable i.e., feedback signal 703 value becomes equal to set point value 701. The controller 703 includes three control operations that are proportional 704, integral 705 and derivative 706 control. The coefficients of these three control actions (proportional, integral, and derivative) are varied to achieve an optimal acceleration based current limit. The controller 703 input is an error signal 702, and the output is sent to the plant or MCU. The controller output signal 707 is generated such that the plant or MCU output tries to achieve the desired set point 701 motor acceleration. In one of the embodiments, the current modulation or control algorithm may be implemented on a Vehicle Control Unit (VCU) and the control system 700 may reside inside the VCU. The input of the control system 700 would be an error signal which is the vehicle/motor acceleration difference as shown in equation 3 of the present subject matter. Further, the vehicle acceleration is obtained through the Motor Control Unit by observing the motor revolution per minute (RPM) and followed by determining the vehicle speed as shown in equation 5 of the present subject matter. The vehicle acceleration is obtained using the monitored vehicle speed from equation 5 according to equation 4 as shown below.
Mathematical calculations for the different parameters as required by the Proportional, Integral, Derivative (PID) controller are shown below:
Acceleration_Current_Limit_A = (Proportional_Gain * Vehicle_Acceleration_Error_m/s2)...
+(Derivative_Gain * d/dt(Vehicle_Acceleration_Error_m/s2)) (Equation 2)
Vehicle_Acceleration_Error_m/s2 = Vehicle_Acceleration_Limit_m/s2 - Vehicle_Acceleration_m/s2
(Equation 3)
Vehicle_Acceleration_m/s2 = d/dt(Motor_Speed_rad/s)*Wheel_Radius_m
(Equation 4)
Motor_Speed_rad/s = Motor_Speed_RPM*(2*3.14/60)
(Equation 5)

In an alternate embodiment of the system 600 as shown in Figure 6a, a single processor core along with a memory storing instructions to perform different steps of the current modulation may be implemented. For instance, a processor core may be configured with memory to perform all the operations performed by a VCU, an MCU and a BMS subsystem. In one such embodiment, the system 600 may be implemented as shown in Figure 6b which includes at least one processor 612, an input/output (I/O) interface 614, and a memory 613. The at least one processor 612 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, Central Processing Units (CPUs), state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, at least one processor 612 is configured to fetch and execute computer-readable instructions stored in the memory 613.
The I/O interface 614 may include a variety of interfaces, for example, in-vehicle communication interface, a telematic unit interface to connect to an external world via internet or wired communication interface and the like. The I/O interface 614 may allow the system 611 to interact with the various in-vehicle subsystems. Further, the I/O interface 614 may enable the system 611 to communicate with other onboard controllers, such as an MCU, a VCU, a BMS and the like via the CAN bus.
The memory 613 may include any computer-readable medium or computer program product known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, Solid State Disks (SSD), optical disks, and magnetic tapes. The memory 613 may include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. The memory 613 may include programs or coded instructions that supplement applications and functions of the system 611. In one embodiment, the memory 613, amongst other things, serves as a repository for storing data processed, received, and generated by one or more of the programs or the coded instructions.
In another embodiment, the system 611 as shown in Figure 6b may be implemented with a single processor including multiple cores to perform the multiple operations of various vehicle subsystems through multiple cores. For example, in the multi core processor system one core may be implemented to operate as a Motor Control Unit and second core may be implemented to operate as a Vehicle Control Unit, third core can be implemented as a Battery Management System.
In an alternate embodiment, a system for controlling a discharge of an electric current in a Battery Driven Vehicle (BDV) may be implemented using multiple subsystems in the form of different control units. The system includes a first control unit for monitoring a real-time speed of the vehicle. The first control unit may be implemented as a Motor Control Unit (MCU). The MCU would be capable of interacting with multiple vehicle subsystems such as a Vehicle Control Unit (VCU) via a CAN bus. A second control unit is utilized for determining an instantaneous acceleration of the vehicle in real time using the monitored speed of the vehicle. The second control unit may be implemented as a Vehicle Control Unit (VCU). The VCU interacts with multiple vehicle subsystems such as a Motor Control Unit (MCU), Battery Management System (BMS) via a CAN bus. The VCU determines the instantaneous acceleration of the vehicle based on the monitored motor speed received at VCU from MCU via the CAN bus.
Further, a third control unit is utilized for determining a State of Charge (SoC) of the battery. The third control unit may be implemented as a Battery Management System (BMS). The BMS typically monitors the battery operations and ensures the vehicle and end user safety. Subsequently, the second control unit i.e., the VCU dynamically controls an amount of electric current discharged from the battery based on the determined instantaneous acceleration of the vehicle. Further, a maximum amount of electric current discharged from the battery is based on the determined State of Charge (SoC) of the battery. Based on the existing ride mode of the vehicle, an acceleration based current limit is determined by the VCU.
In an alternate embodiment, the system may comprise multiple Internet of things (IoT) based sensors that may provide different in vehicle parameters to a cloud or a server. The different parameters such as monitored vehicle speed, State of Charge (SoC) of a battery, existing ride mode of the vehicle, and any other vehicle operating conditions might be transmitted to the cloud or server. In one embodiment, the vehicle related parameters may be sent via a wireless communication network to the cloud or server. The wireless communication network may be used from a plurality of networks such as, cellular networks, wireless local area networks, wireless sensor networks, satellite communication networks and terrestrial microwave networks. The cloud or server would receive the vehicle related parameters and subsequently may transmit a relevant control command/signal to the vehicle. The command/signal from the cloud or server may be received by a vehicle telematics unit to take an appropriate action . In one embodiment, the action taken may include limiting the maximum current that the battery may discharge while the vehicle is in operation.
In another embodiment, for determining an acceleration based current limit, a ride mode of the vehicle may be selected automatically. The ride mode of a vehicle may be selected automatically by the vehicle subsystem for instance by the Vehicle Control Unit (VCU) 502 by applying machine learning techniques. For example, a machine learning algorithm or Artificial Neural Networks (ANN) may be used to enable the system to predict an appropriate ride mode for the vehicle based on the past historical data of one or more user profiles. The user profile data may be saved locally on the vehicle itself or may be obtained from a cloud or server via an internet connectivity.
For training the machine learning models a labelled dataset may be used which provides different user profiles including details such as age, gender, user’s past riding behaviour like speed, average speed, ride time, navigation data such as route navigated or preferred, travel time on the ride, distance covered, travel timings etc. The riding history data of users are saved along with labelled ride modes, corresponding to each riding session of a particular user. A machine learning technique such as artificial neural networks may be utilized to first train the prediction model using this labelled data set. Further, a preferred output ride mode may be automatically selected by the vehicle or recommended to the user.
Referring now to Figure 8 that illustrates an example of an artificial neural network (“ANN”) 800 of the deep learning algorithms. In an exemplary embodiment, an ANN may refer to a computational model comprising one or more nodes. Example ANN 800 may comprise an input layer 810, hidden layers 820, 830, 860, and an output layer 850. Each layer of the ANN 800 may comprise one or more nodes, such as a node 805 or a node 815. In particular embodiments, each node of an ANN may be connected to another node of the ANN. As an example, and not by way of limitation, each node of the input layer 810 may be connected to one or more nodes of the hidden layer 820. In particular embodiments, one or more nodes may be a bias node (e.g., a node in a layer that is not connected to and does not receive input from any node in a previous layer). In particular embodiments, each node in each layer may be connected to one or more nodes of a previous or subsequent layer. Although Figure 8 depicts a particular ANN with a particular number of layers, a particular number of nodes, and particular connections between nodes, this disclosure contemplates any suitable ANN with any suitable number of layers, any suitable number of nodes, and any suitable connections between nodes. As an example, and not by way of limitation, although Figure 8 depicts a connection between each node of the input layer 810 and each node of the hidden layer 820, one or more nodes of the input layer 810 may not be connected to one or more nodes of the hidden layer 820.
In particular embodiments, an ANN may be a feedforward ANN (e.g., an ANN with no cycles or loops where communication between nodes flows in one direction beginning with the input layer and proceeding to successive layers). As an example, and not by way of limitation, the input to each node of the hidden layer 820 may comprise the output of one or more nodes of the input layer 810. As another example and not by way of limitation, the input to each node of the output layer 850 may comprise the output of one or more nodes of the hidden layer 860. In particular embodiments, an ANN may be a deep neural network (e.g., a neural network comprising at least two hidden layers). In particular embodiments, an ANN may be a deep residual network. A deep residual network may be a feedforward ANN comprising hidden layers organized into residual blocks. The input into each residual block after the first residual block may be a function of the output of the previous residual block and the input of the previous residual block. As an example, and not by way of limitation, the input into residual block N may be F(x)+x, where F(x) may be the output of residual block N−1, x may be the input into residual block N−1. Although this disclosure describes a particular ANN, this disclosure contemplates any suitable ANN.
In particular embodiments, an activation function may correspond to each node of an ANN. An activation function of a node may define the output of a node for a given input. In particular embodiments, an input to a node may comprise a set of inputs. As an example, and not by way of limitation, an activation function may be an identity function, a binary step function, a logistic function, or any other suitable function.
In particular embodiments, the input of an activation function corresponding to a node may be weighted. Each node may generate output using a corresponding activation function based on weighted inputs. In particular embodiments, each connection between nodes may be associated with a weight. As an example, and not by way of limitation, a connection 825 between the node 805 and the node 815 may have a weighting coefficient of 0.4, which may indicate that 0.4 multiplied by the output of the node 805 is used as an input to the node 815. In particular embodiments, the input to nodes of the input layer may be based on a vector representing an object. Although this disclosure describes particular inputs to and outputs of nodes, this disclosure contemplates any suitable inputs to and outputs of nodes. Moreover, although this disclosure may describe particular connections and weights between nodes, this disclosure contemplates any suitable connections and weights between nodes.
In particular embodiments, the ANN may be trained using training data. As an example, and not by way of limitation, training data may comprise inputs to the ANN 800 and an expected output. As another example and not by way of limitation, training data may comprise vectors each representing a training object and an expected label for each training object. In particular embodiments, training the ANN may comprise modifying the weights associated with the connections between nodes of the ANN by optimizing an objective function. As an example, and not by way of limitation, a training method may be used (e.g., the conjugate gradient method, the gradient descent method, the stochastic gradient descent) to backpropagate the sum-of-squares error measured as a distance between each vector representing a training object (e.g., using a cost function that minimizes the sum-of-squares error). In particular embodiments, the ANN may be trained using a dropout technique. As an example, and not by way of limitation, one or more nodes may be temporarily omitted (e.g., receive no input and generate no output) while training. For each training object, one or more nodes of the ANN may have some probability of being omitted. The nodes that are omitted for a particular training object may be different than the nodes omitted for other training objects (e.g., the nodes may be temporarily omitted on an object-by-object basis). Although this disclosure describes training the ANN in a particular manner, this disclosure contemplates training the ANN in any suitable manner.
Exemplary embodiments discussed above may provide certain advantages. Though not required to practice aspects of the disclosure, these advantages may include those provided by the following features.
The system and the method disclosed in different embodiments does not require a measurement system such as an inertial measurement system to calculate a load on the vehicle to change the maximum torque limit.
The system and the method disclosed in different embodiments does not require any additional sensor apart from the actuator or motor rotational speed sensor.
The system and the method disclosed in different embodiments allows users to save on efficiency loss while also overcoming high torque demand situations such as heavily loaded conditions without changing any of the vehicle settings during driving.
The system and the method disclosed in different embodiments consumes lesser electronic control units, memory, and processing power.
Although implementations for methods and systems for controlling or modulating discharge of an electric current in a Battery Driven Vehicle (BDV) have been described in language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations for controlling discharge of an electric current in a Battery Driven Vehicle (BDV). , Claims:We Claim:
1. A method for controlling discharge of an electric current in a Battery Driven Vehicle (BDV) comprising:
monitoring, in real-time, a speed of the vehicle;
determining, in real time, an instantaneous acceleration of the vehicle using the monitored speed of the vehicle;
determining a State of Charge (SoC) of a battery;
dynamically controlling an amount of electric current discharged from the battery based on the determined instantaneous acceleration of the vehicle, wherein a maximum amount of electric current discharged from the battery is based on the determined SOC.
2. The method as claimed in claim 1, wherein the maximum amount of electric current discharged from the battery is based on a ride mode of the vehicle.
3. The method as claimed in claim 1, wherein the amount of electric current discharged from the battery is dynamically controlled by a Vehicle Control Unit (VCU).
4. The method as claimed in claim 1, wherein a maximum acceleration is applied to a measured value of the vehicle speed.
5. The method as claimed in claim 4, wherein the maximum acceleration of the vehicle depends on the ride mode of the vehicle.
6. The method as claimed in claim 5, wherein a acceleration based current limit is determined based on the maximum acceleration of the vehicle according to the ride mode of the vehicle.
7. The method as claimed in claim 1, wherein the State of Charge (SoC) is obtained from a Battery Management System (BMS) to determine the State of Charge (SoC) based current limit.
8. The method as claimed in claim 7, wherein the State of Charge (SoC) based current limit and the acceleration based current limit is utilized to calculate a combined current limit.
9. The method as claimed in claim 8, wherein the combined current limit indicates a peak current limit that can be drawn by a Motor Control Unit (MCU) to drive a motor.
10. The method as claimed in claim 9, wherein the peak current limit determines a maximum torque delivered by the motor during operation.
11. A system for controlling discharge of an electric current in a Battery Driven Vehicle (BDV) comprising:
a memory; and
a processor coupled to the memory, wherein the processor is configured to execute instructions stored in the memory for:
monitoring, by the processor, a speed of the vehicle in real-time;
determining, by the processor, an instantaneous acceleration of the vehicle in real time using the monitored speed of the vehicle;
determining, by the processor, a State of Charge (SoC) of a battery;
dynamically, controlling by the processor, an amount of electric current discharged from the battery based on the determined instantaneous acceleration of the vehicle, wherein a maximum amount of electric current discharged from the battery is based on the determined SOC.
12. The system as claimed in claim 11, wherein the maximum amount of electric current discharged from the battery is based on a ride mode of the vehicle.
13. The system as claimed in claim 11, wherein the amount of electric current discharged from the battery is dynamically controlled by a Vehicle Control Unit (VCU).
14. The system as claimed in claim 11, wherein a maximum acceleration is applied to a measured value of the vehicle speed.
15. The system as claimed in claim 14, wherein the maximum acceleration allowed depends on the ride mode of the vehicle.
16. The system as claimed in claim 15, wherein a acceleration based current limit is determined based on the maximum acceleration of the vehicle based on the ride of the vehicle.
17. The system as claimed in claim 11, wherein the State of Charge (SoC) is obtained from a Battery Management System (BMS) to determine the State of Charge (SoC) based current limit.
18. The system as claimed in claim 17, wherein the State of Charge (SoC) based current limit and the acceleration based current limit is utilized to calculate a combined current limit.
19. The system as claimed in claim 18, wherein the combined current limit indicates a peak current limit that can be drawn by a Motor Control Unit (MCU) to drive a motor.
20. The system as claimed in claim 29, wherein the peak current limit determines a maximum torque delivered by the motor during operation.
21. A system for controlling discharge of an electric current in a Battery Driven Vehicle (BDV) comprising:
a first control unit, for monitoring a speed of the vehicle in real time;
a second control unit, for determining an instantaneous acceleration of the vehicle in real time using the monitored speed of the vehicle;
a third control unit, determining a State of Charge (SoC) of the battery and dynamically controlling an amount of electric current discharged from the battery based on the determined instantaneous acceleration of the vehicle by the second control unit, wherein a maximum amount of electric current discharged from the battery is based on the determined State of Charge (SoC).
22. The system as claimed in claim 21, wherein the first control unit is a Motor Control Unit (MCU), the second control unit is a Vehicle Control Unit (VCU) and the third control unit is Battery Management System (BMS).
23. The system as claimed in claim 22, wherein the maximum amount of electric current discharged from the battery is based on a ride mode of the vehicle.