Claims:We claim:
1. A method (200) for managing operation of a vehicle (20), the method (200) comprising:
determining, by a control system (100), an energy of the vehicle (20) based on a first parameter and a second parameter, wherein the first parameter is received from an electronic control unit (ECU) (102), where the second parameter is associated with a specification of the vehicle (20); and
identifying, by the control system (100), an overall weight of the vehicle (20) based on the determined energy.

2. The method (200) as claimed in claim 1, wherein the method (200) includes,
determining, by the control system (100), an average velocity associated with the vehicle (20) based on the first parameter; and
selecting, by the control system (100), at least one of a driving mode from a plurality of driving modes, and a driver profile from a plurality of driver profiles based on the identified weight of the vehicle (20) and the determined average velocity.

3. The method (200) as claimed in claim 2, wherein the method (200) includes,
performing, by the control system (100), at least one action based on the selected driving mode and driver profile, wherein the action corresponds to identify a torque requirement, maximum revolution per minute (RPM) requirement of a power source of the vehicle (20), control a maximum torque in the driving mode and control a rate at which a torque to be delivered in the driving mode.
4. The method (200) as claimed in claim 1, wherein the first parameter includes at least one of a torque of one of a power source and a power transmission unit (gearbox), a speed of the vehicle (20), a gear information, a revolution per minute (RPM) associated with the power source, an accelerator pedal position, a brake signal, a clutch signal, and a gradient sensor information, wherein the second parameter comprises at least one of a tire specification and a transmission specification.

5. The method (200) as claimed in claim 1, wherein said identifying, by the control system (100), the overall weight of the vehicle (20) includes,
comparing, by the control system (100), the energy requirement by the vehicle (20) with the second parameter; and
identifying, by the control system (100), the overall weight of the vehicle (20) based on the comparison.

6. The method (200) as claimed in claim 1, wherein the weight of the vehicle (20) is identified without using a load sensor module (load cell).

7. A control system (100) for managing operation of a vehicle (20), the control system (100) comprising:
at least one electronic control unit (ECU) (102);
a memory (110);
a processor (106); and
a load detection and mode detection controller (104) coupled with the memory (110), the processor (106) and the ECU (102), where the load detection and mode detection controller (104) is configured to:
determine an energy of the vehicle (20) based on a first parameter and a second parameter, wherein the first parameter is received from the ECU (102) and the second parameter is associated with a specification of the vehicle (20), and
identify a weight of the vehicle (20) based on the determined energy.

8. The control system (100) as claimed in claim 7, wherein the load detection and mode detection controller (104) is configured to:
determine an average velocity associated with the vehicle (20) based on the first parameter; and
select at least one of a driving mode from a plurality of driving modes and a driver profile from a plurality of driver profiles based on the identified weight of the vehicle (20) and the determined average velocity.

9. The control system (100) as claimed in claim 8, wherein the load detection and mode detection controller (104) is configured to perform at least one action based on the selection, wherein the action corresponds to identify a torque requirement, maximum revolution per minute (RPM) requirement, control a maximum torque in the driving mode, control a rate at which a torque to be delivered in the driving mode, and control a maximum speed of each gear in the driving mode.

10. The control system (100) as claimed in claim 7, wherein the first parameter comprises at least one of a torque of one of a power source and a power transmission unit (gearbox), a speed of the vehicle (20), a gear information, a revolution per minute (RPM) associated with the power source, an accelerator pedal position, a brake signal, a clutch signal, and a gradient sensor information, wherein the second parameter includes at least one of a tire specification and a transmission specification.

11. The control system (100) as claimed in claim 7, wherein identify the weight of the vehicle (20) includes,
compare the energy requirement by the vehicle (20) with the second parameter; and
identify the weight of the vehicle (20) based on the comparison.

12. The control system (100) as claimed in claim 7, wherein the weight of the vehicle (20) is identified without using a load sensor module (load cell).
, Description:TECHNICAL FIELD
[001] Embodiments herein generally relate to a vehicle operation management system and more particularly, to a method and a control system for load detection of the vehicle and for selecting driving mode in the vehicle in accordance to the detected load of the vehicle, where the load of the vehicle is detected automatically without using a load sensor (e.g., load cell or the like).

BACKGROUND
[002] For a vehicle, fuel efficiency is one of a key target for a customer. The cargo carrying vehicle will run ‘completely loaded’ on one side and in return, the vehicle will come with 'less load'. This scenario will give high accelerations during 'low load' conditions and low accelerations during 'high load' conditions. In existing methods, the vehicle can be used to determine the load detection/weight detection in the vehicle using a load cell. This is expensive.
[003] Thus, it is desired to address the above mentioned disadvantages or other shortcomings or at least provide a useful alternative.

OBJECTS
[004] The principal object of the embodiments herein is to disclose a system for load detection of a vehicle and for selecting a driving mode in the vehicle in accordance to the detected load of the vehicle, where the load of the vehicle is detected automatically without using a load sensor (e.g., load cell or the like).
[005] Another object of the embodiments herein is to disclose a method for load detection of the vehicle and for selecting a driving mode in the vehicle in accordance to the detected load of the vehicle.
[006] Another object of the embodiments herein is to determine an energy of the vehicle based on a first parameter and a second parameter, where the first parameter is received from an electronic control unit (ECU), where the electronic control unit (ECU) is one of a vehicle control unit and an Engine Control Unit (ECU) (e.g., Engine Management System Engine Control Unit (EMS ECU)), and the second parameter is associated with a specification of the vehicle.
[007] Another object of the embodiments herein is to identify a weight of the vehicle based on the determined energy.
[008] Another object of the embodiments herein is to dynamically detect a weight of the vehicle during vehicle running conditions without the usage of any load sensor (e.g., load cell) in a cost effective manner.
[009] Yet, another object of the embodiments herein is to determine out a better driving mode for the vehicle and communicate to a vehicle ECU depending on a vehicle load in an automatic manner.
[0010] Yet, another object of the embodiments herein is to define a driving mode depending on vehicle weight to improve a fuel efficiency and drivability of the vehicle.
[0011] These and other objects of embodiments herein will be better appreciated and understood when considered in conjunction with following description and accompanying drawings. It should be understood, however, that the following descriptions, while indicating embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF FIGURES
[0012] Embodiments herein are illustrated in the accompanying drawings, through out which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0013] FIG. 1 illustrates various hardware elements in a vehicle for load detection and driving mode detection, according to embodiments as disclosed herein;
[0014] FIG. 2 is a flow chart illustrating a method for load detection and driving mode detection in the vehicle, according to embodiments as disclosed herein; and
[0015] FIG. 3 shows an example graph illustrating a torque delivery with different loads, according to embodiments as disclosed herein.

DETAILED DESCRIPTION
[0016] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0017] The terms “vehicle operating condition”, “mode detection”, and “driving mode” are used interchangeably in the patent disclosure.
[0018] Embodiments herein disclose a method for managing operation of a vehicle. The method includes determining, by the control system, an energy of the vehicle based on a first parameter and a second parameter. The first parameter is received from an ECU and the second parameter is associated with a specification of the vehicle. Further, the method includes identifying, by the control system, an overall weight of the vehicle based on the determined energy. Further, the method includes determining, by the control system, an average velocity associated with the vehicle based on the first parameter. Further, the method includes selecting, by the control system, at least one of a driving mode from a plurality of driving modes and a driver profile from a plurality of driver profiles based on the identified weight of the vehicle and the determined average velocity.
[0019] Unlike conventional methods and vehicles, the method can be used to detect the weight of the vehicle during vehicle running conditions without the usage of any load sensor module (load cell) in a cost effective manner. Further, the method can be used to determine out a best driving mode for the vehicle and communicate to a vehicle ECU depending on a vehicle load in an automatic manner. Further, the method can be used to define a driving mode depending on vehicle weight to improve a fuel efficiency and drivability of the vehicle.
[0020] In the proposed method, for the vehicle, depending upon the vehicle weight, the different driving modes will be selected automatically. This will be done without driver intervention to improve the fuel efficiency/drivability of the vehicle.
[0021] Referring now to the drawings, and more particularly to FIGS. 1 through 3, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.
[0022] FIG. 1 illustrates various hardware elements in a vehicle (20) for load detection and drive mode selection, according to embodiments as disclosed herein. The vehicle (20) can also be, for example, but not limited to a car, a truck, a van, a lorry, a bus, or the like. The vehicle (20) can also be, for example, but not limited to an electrical vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicles (PHEV), a battery based electric vehicle (BEV) or the like. In an embodiment, the system (100) includes at least one electronic control unit (ECU) (102), a load detection and mode detection controller (104), a processor (106), a communicator (108) and a memory (110). The electronic control unit (ECU) (102) is one of a vehicle controller unit and an engine management system engine control unit (EMS ECU).
[0023] The load detection and mode detection controller (104) is configured to determine an energy of the vehicle (20) based on a first parameter and a second parameter. The first parameter is received from the ECU (102) and the second parameter is associated with a specification of the vehicle (20). The first parameter can be, for example, but not limited to a torque of at least one of a power source and a power transmission unit (gearbox), a speed of the vehicle (20), a gear information, a revolution per minute (RPM) associated with the power source (engine), an accelerator pedal position, a brake signal, a clutch signal, and a gradient sensor information. For the purpose of this description and ease of understanding, the power source is considered to be one of an engine and an electric motor. The second parameter can be, for example, but not limited to a tire specification and a transmission specification. In an example, the load detection and mode detection controller (104) communicates with the ECU (102) through a controller area network (CAN) protocol and the ECU (102) is providing signals like torque of at least one of the power source and the power transmission unit (gearbox), the speed of the vehicle (20), the gear information, revolution per minute (RPM) associated with the power source (engine), the accelerator pedal position, the brake signal, the clutch signal, and the gradient sensor information. Further, the signals obtaining from the ECU (102) has been filtered and averaged for further determination by using the load detection and mode detection controller (104).
[0024] Based on the determined energy, the load detection and mode detection controller (104) is configured to identify a weight/load of the vehicle (20). In an example, the load detection and mode detection controller (104) calculates the cumulative energy generated by the power source (engine (not shown)) over a period based on the first parameter and the second parameter. Further, the energy requirement by the vehicle (20) will be compared against the vehicle specifications to determine the weight of the vehicle (20) by using the load detection and mode detection controller (104). The driver profile may be generated and/or modified using vehicle telematics data indicative of how the driver drives the vehicle (20) based on various data (e.g., acceleration data, braking data, Global Positioning System (GPS) data, sensor data indicating presence of passengers in the vehicle (20), distance between the driver's vehicle and other vehicles, weather, demographic information, dealership information regarding maintenance or the like). The driver profile may include personal information (e.g., gender, age, education level, profession, disabilities/impairments/limitations, etc.) and vehicle information (e.g., vehicle model, year, and/or colour of the vehicle (20) or the like. The driver profile includes information, including a plurality of settings, relating to, or defining aspects of, the operation of the vehicle (20). The plurality of settings can be, for example, but not limited to preferences for stronger or weaker acceleration, for faster or slower driving through curves, for cutting or not cutting curves, for harder or softer braking. The driver profile can include settings for almost any driving characteristic bounded by applicable safety standards and laws.
[0025] Further, the load detection and mode detection controller (104) is configured to determine an average velocity associated with the vehicle (20) based on the first parameter. Further, the load detection and mode detection controller (104) is configured to select one or more driving mode from the plurality of driving modes and one or more driver profile from the plurality of driver profiles based on the identified weight of the vehicle (20) and the determined average velocity. The driving mode can be, for example, but not limited to an autonomous driving mode, a manual driving mode, a semi-autonomous driving mode, an eco-friendly driving mode, a sport driving mode, a race driving mode, an engine drive mode, an electric drive mode, hybrid drive mode, or the like.
[0026] In an embodiment, weight of the vehicle (20) is identified by comparing the energy requirement by the vehicle (20) with the second parameter and identifying the weight of the vehicle (20) based on the comparison. In an example, depending on the weight of the vehicle (20) and the average speed of the vehicle (20), the user of the vehicle (20) confirms and switch between the driving modes. Further, depending on the mode selected above the predefined values will be set for torque delivery from one of power source (engine and/or electric motor) and power transmission unit (gearbox)). This will mainly control the maximum torque in each mode, the rate at which the torque to be delivered, and the maximum speed of each gear. This will be communicated back to the ECU (102) through the CAN communication.
[0027] Unlike conventional vehicles and methods, in the proposed method, the weight of the vehicle (20) is identified without using any load sensor module (load cell). Hence, the control system (100) can detect the best driving mode of the vehicle (20) for the vehicle speed and the driver profile in an automatic manner. Further, the vehicle (20) can run in the best fuel efficiency mode automatically.
[0028] In the proposed method, for the vehicle (20), depending upon the vehicle weight, the different driving modes will be selected automatically. This will be done without driver intervention to improve the fuel efficiency/drivability of the vehicle (20).
[0029] The control system (100) will automatically detect the best driving mode for the vehicle (20) and will send the signal to the ECU to control the torque and speed of one of the power source and the power transmission unit to achieve pre-defined values. As per the load on the vehicle (20) different driving modes will be selected automatically. The driver feels and accelerations has kept same irrespective of the driving modes. The time taken to achieve a particular vehicle speed kept identical between the driving modes as per the table 1.

[0030] The table 1 indicates the performance with different loads.
Vehicle Speed [km/hr] Heavy Load [Sec] Medium load [Sec] No-load
[Sec]
20-30 km/hr t1 t1 t1
20-50 km/hr t2 t2 t2
20- 80 km/hr t3 t3 t3
Table 1
[0031] The load detection and mode detection controller (104) is physically implemented by analog or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits, or the like, and may optionally be driven by firmware.
[0032] Further, the memory (110) also stores instructions to be executed by the processor (106). The memory (110) may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. In addition, the memory (110) may, in some examples, be considered a non-transitory storage medium. The term “non-transitory” may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term “non-transitory” should not be interpreted that the memory (110) is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache).
[0033] Further, the processor (106) is configured to execute instructions stored in the memory (110) and to perform various processes. The communicator (108) is configured for communicating internally between internal hardware components and with external devices via one or more networks.
[0034] The processor (106) may include one or a plurality of processors. At this time, one or a plurality of processors may be a general purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an AI-dedicated processor such as a neural processing unit (NPU).
[0035] The one or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model or a machine learning (ML) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence (AI) model is provided through training or learning.
[0036] The AI model may consist of a plurality of neural network layers. Each layer has a plurality of weight values, and performs a layer operation through calculation of a previous layer and an operation of a plurality of weights. Examples of neural networks include, but are not limited to, convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), restricted Boltzmann Machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), generative adversarial networks (GAN), and deep Q-networks.
[0037] FIG. 1 shows exemplary units of the vehicle (20), but it is to be understood that other embodiments are not limited thereon. In other embodiments, the vehicle (20) may include less or more number of units. Further, the labels or names of the units of the vehicle (20) are used only for illustrative purpose and does not limit the scope of the invention. One or more units can be combined together to perform same or substantially similar function in the vehicle (20).
[0038] FIG. 2 is a flow chart (S200) illustrating a method for load detection and drive mode selection in the vehicle (20), according to embodiments as disclosed herein. The operations (i.e., Step 202-Step 216) are performed by the load detection and mode detection controller (104).
[0039] At Step 202, the method (200) includes acquiring the first parameter. In an example, the load detection and mode detection controller (104) communicates with the ECU (102) through the CAN protocol and the ECU (102) is providing signals like torque of at least one of the power source and the power transmission unit (gearbox), the speed of the vehicle (20), the gear information, the revolution per minute (RPM) associated with the power source (engine), the accelerator pedal position, the brake signal, the clutch signal, and the gradient sensor information.
[0040] At Step 204, the method (200) includes acquiring the second parameter. At Step 206, the method (200) includes preprocessing the first parameter. In an example, the signals obtaining from the ECU (102) has been filtered and averaged for further determination by using the load detection and mode detection controller (104).
[0041] At Step 208, the method (200) includes determining the energy of the vehicle based on the preprocessed first parameter and the second parameter. In an example, the load detection and mode detection controller (104) calculates the cumulative energy generated by the engine over the period based on the first parameter and the second parameter.
[0042] At Step 210, the method (200) includes identifying the weight of the vehicle (20) in response to determining the energy of the vehicle (20). In an example, the energy requirement by the vehicle (20) will be compared against the vehicle specifications to determine the weight of the vehicle (20) by using the load detection and mode detection controller (104).
[0043] At Step 212, the method (200) includes determining the average velocity associated with the vehicle (20) based on the first parameter. At Step 214, the method (200) includes selecting the driving mode from the plurality of driving modes and the driver profile from the plurality of driver profiles based on the based on the identified weight of the vehicle (20) and the determined average velocity. In an example, depending on the weight of the vehicle (20) and the average speed of the vehicle (20), the user of the vehicle (20) confirms and switch between the driving modes.
[0044] At Step 216, the method (200) includes performing one or more action based on the driving mode selection. The action corresponds to identify the torque requirement, maximum RPM requirement, control the maximum torque in the driving mode, control the rate at which a torque to be delivered in the driving mode, and control the maximum speed of each gear in the driving mode. In an example, depending on the driving mode selected above the predefined values will be set for torque delivery. This will mainly control the maximum torque in each mode, the rate at which the torque to be delivered, and the maximum speed of each gear. This will be communicated back to the ECU (102) through the CAN communication.
[0045] Unlike conventional methods and vehicles, the method (200) can be used to detect the weight of the vehicle (20) during vehicle running conditions without the usage of any load cells in a cost effective manner. Further, the method (200) can be used to determine out the best driving mode for the vehicle (20) and communicate to the vehicle ECU depending on the vehicle load. Further, the method (200) can be used to define the driving modes depending on the vehicle weight to improve the fuel efficiency and drivability.
[0046] The various actions, acts, blocks, steps, or the like in the flow chart (S200) may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.
[0047] FIG. 3 shows an example graph (300) illustrating a torque delivery with different loads, according to embodiments as disclosed herein. In the FIG. 3, the maximum torque from the engine with respect to different RPM is given. According to the automatic mode detection on the vehicle (20), the maximum torque at different rpm will be changed as per the FIG. 3.
[0048] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The elements shown in FIG. 1 include blocks which can be at least one of a hardware device, or a combination of hardware device and software module.
[0049] The embodiments disclosed herein describe load detection and drive mode detection in the vehicle (20). Therefore, it is understood that the scope of the protection is extended to such a program and in addition to a computer readable means having a message therein, such computer readable storage means contain program code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The method is implemented in a preferred embodiment through or together with a software program written in example Very high speed integrated circuit Hardware Description Language (VHDL), or any other programming language, or implemented by one or more VHDL or several software modules being executed on at least one hardware device. The hardware device can be any kind of portable device that can be programmed. The device may also include means, which could be, for example, a hardware means, for example, an Application-specific Integrated Circuit (ASIC), or a combination of hardware and software means, for example, an ASIC and a Field Programmable Gate Array (FPGA), or at least one microprocessor and at least one memory with software modules located therein. The method embodiments described herein could be implemented partly in hardware and partly in software. Alternatively, the invention may be implemented on different hardware devices, e.g. using a plurality of Central Processing Units (CPUs).
[0050] The technical advantages of the control system (100) for load detection and driving mode selection are as follows. The control system (100) dynamically detects a weight of the vehicle during vehicle running conditions without the usage of any load sensor (e.g., load cell) in a cost effective manner. The control system (100) determines a better driving mode for the vehicle and communicates to a vehicle ECU depending on a vehicle load in an automatic manner. The control system (100) selects driving mode depending on vehicle weight to improve a fuel efficiency and drivability of the vehicle.
[0051] 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 scope of the embodiments as described herein.