ADJUSTMENT AND MONITORING FUNCTION FOR JERK DAMPER PARAMETERS IN CLOSED CONTROL LOOP

Abstract

The present disclosure relates to a method and system for closed-loop adjustment of shudder parameters in a vehicle. The method includes receiving at least one of a vehicle speed, an engine speed, and a moving average damped engine speed of the vehicle. Thereafter, the method includes updating a powertrain model to replicate the real-world powertrain of the vehicle based on at least one of the vehicle speed, the engine speed, and the moving average damped engine speed of the vehicle to obtain engine speed fluctuations. Thereafter, the method includes determining a shudder gain and a shudder cutoff frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed fluctuations.Finally, the method includes transmitting the judder damper gain and the judder damper cut-off frequency to an engine control device of the vehicle to determine a damping torque.

Description

PREAMBLE TO DESCRIPTION:The following specification describes in particular the invention and the manner in which it is to be practiced:DESCRIPTION OF THE INVENTIONTechnical FieldThe present disclosure relates to the field of vehicles. More particularly, but not specifically, the present disclosure relates to a method and system for adjusting and monitoring closed loop shock absorber parameters in a vehicle.RELATED ART OF DISCLOSUREIn vehicles, anti-jerk control devices use engine speed as a variable for calculating a correction torque for the powertrain. In addition, filter parameters such as a gain and a cut-off frequency are used for calculating the correction torque. In current vehicles, the gain and shut-down frequency are constant or static for all torque transients. As a result, calculating the powertrain correction torque does not enable dynamic correction of driveline jerks or oscillations caused by powertrain aging or manufacturing differences in vehicle components during the life of the vehicle.The information disclosed in this background section of the disclosure is only for enhancement of understanding of the general background art of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.BRIEF DESCRIPTION OF THE DISCLOSUREIn one embodiment, the present disclosure relates to a method for adjusting the shock absorber parameters in a closed loop vehicle. The method includes receiving, by a transceiver of a system, at least one of a vehicle speed, an engine speed, and a moving average attenuated engine speed of the vehicle. Thereafter, the method includes updating the powertrain model of the system with a powertrain model to mimic the real powertrain of the vehicle based on at least one of the vehicle speed, the engine speed, and the moving average attenuated engine speed of the vehicle to obtain engine speed variations. Subsequently, the method includes determining, by an anti-jerk controller model of the system, a jerk damper gain and frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed oscillations. Finally, the method includes transmitting, by the transceiver, the jerk damper gain and the jerk damper cut-off frequency to an engine control device of the vehicle to determine a damping torque.In one embodiment, the present disclosure relates to a system for adjusting the shock absorber parameters in a closed loop vehicle. The system includes a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions that, when executed, cause the processor to receive at least one of a vehicle speed, an engine speed, and a moving average attenuated engine speed of the vehicle. Thereafter, the processor is configured to update a powertrain model to mimic the real-world powertrain of the vehicle based on at least one of the vehicle speed, the engine speed, and the moving average attenuated engine speed of the vehicle to obtain engine speed variations. Subsequently, the processor is configured to determine a jerk damper gain and a jerk damper deactivation frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed variations. Finally, the processor is configured to transmit the shock absorber gain and the shock absorber cut-off frequency to an engine control device of the vehicle to determine a damping torque.The foregoing summary is illustrative only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, other aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.BRIEF DESCRIPTION OF THE DRAWINGSThe novel features and characteristics of the disclosure are set forth in the appended claims. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and together with the description, serve to explain the disclosed principles. In the figures, the leftmost digit(s) of a reference numeral indicates the figure in which the reference numeral appears first. Throughout the figures, the same numbers are used to indicate like features and components. Some embodiments of systems and / or methods according to embodiments of the present subject matter will now be described below, by way of example only, and with reference to the accompanying figures. FIG. 1 illustrates an example environment for adjusting the closed loop jerk damper parameters of a vehicle, in accordance with some embodiments of the present disclosure. FIG. 2 shows a detailed block diagram of a system for adjusting the closed loop shock absorber parameters of a vehicle, in accordance with some embodiments of the present disclosure. FIG. 3 illustrates a flow chart illustrating a method for adjusting the closed loop shock absorber parameters of a vehicle in accordance with some embodiments of the present disclosure. FIG. 4 illustrates a block diagram of an example computer system for implementing embodiments consistent with the present disclosure.Those skilled in the art should appreciate that all block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that all flowcharts, flowcharts, state transition diagrams, pseudo code, and the like represent various processes, substantially embodied in a computer readable medium, that may be executed by a computer or processor, whether or not such a computer or processor is explicitly shown.DETAILED DESCRIPTIONIn the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration.". Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.While the disclosure is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the figures and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is intended to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.The terms "comprises," "comprising," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a structure, apparatus, and method that / she comprises a list of components not only includes those components, but may also include other components or steps not expressly listed or associated with such structure, apparatus, or method. In other words, one or more elements in a system or device continuing with "comprises... a" does not exclude, without further limitations, the presence of other or additional elements in the system or device.In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is therefore not to be understood as limiting.FIG. 1 illustrates an environment for adjusting the closed loop jerk damper parameters of a vehicle, in accordance with some embodiments of the present disclosure.As shown in FIG. 1, the environment 100 includes a vehicle 101, a communication network 103, a system 105, and a database 113. The vehicle 101 may be a motor vehicle such as, but not limited to, a car, truck, or bus. In one embodiment, the system 105 is part of the vehicle 101 and communicates with the database 113 via the communication network 103. In another embodiment, the system 105 is located on a cloud computing platform or remote location and communicates with the vehicle 101 and database 113 via the communication network 103. For the sake of explanation, only one database 113 is shown in Fig. 1. In practice, however, there may be more than one database 113 (also referred to as one or more sources). Database 113 is located at a remote location or on a cloud computing platform.The communication network 103 may be any of the following communication protocols / methods, but is not limited to a direct connection, an e-commerce network, a peer-to-peer (P2P) network, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using wireless application protocol), the Internet, Wi-Fi, Bluetooth, and the like.In the embodiment, the system 105 includes an input-output (E-A) interface 107, a memory 109, and a processor 111. During the real-time phase or the test phase, the E-A interface 107 is configured to receive from the vehicle 101 at least one of a vehicle speed, an engine speed, or a moving average damped engine speed of the vehicle 101 and transmit a jerk damper gain and a jerk damper shut-off frequency to an engine control device of the vehicle 101 to determine a damping torque. During the training phase, the E-A interface 107 is configured to receive a plurality of historical engine speeds and associated historical vehicle speeds, a plurality of historical sliding average damped engine speeds, and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources, i.e., the database 113. As used herein, the term "historical" refers to past (i.e., historical) data. The E-A interface 107 employs communication protocols / methods such as, without limitation, audio, analog, digital, monaural, Radio Corporation of America (RCA) connectors, stereo, IEEE® 1394 high speed serial bus, serial bus, universal serial bus (USB), infrared, personal system / 2 (PS / 2) port, bayonet neill-concelman (BNC) port, coaxial, component, composite digital visual interface (DVI), high definition multimedia interface (HDMI®), radio frequency (RF) antennas, S-video, Video graphics array (VGA), IEEE® 802.11b / g / n / x, Bluetooth, cellular, for example, code division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM®), long-term evolution (LTE®), worldwide interoperability for microwave access (WiMax®), or the like.The at least one of a vehicle speed, an engine speed, and a moving average attenuated engine speed of the vehicle 101 received from the E-A interface 107 are stored in the memory 109. The memory 109 is communicatively coupled to the processor 111 of the system 105. The memory 109 also stores processor-executable instructions that may cause the processor 111 to execute the instructions for closed-loop adjustment of the shock absorber parameters of the vehicle 101. The memory 109 includes, without limitation, storage drives, removable disk drives, etc. The storage drives may further include a drum, a magnetic disk drive, a magneto-optical drive, an optical drive, a redundant array of independent disks (RAID) architecture, solid state storage devices, solid state drives, etc.The processor 111 includes at least one data processor for adjusting shock absorber parameters in the vehicle 101. The processor 111 may include specialized processing units, such as integrated system (bus) controllers, memory management controllers, floating point units, graphics processing units, digital signal processing units, etc.In one embodiment, the engine control device (not shown in FIG. 1 ) of the vehicle 101 is communicatively coupled to the system 105 via the communication network 103.Database 113 stores a plurality of historical engine speeds and associated historical vehicle speeds, a plurality of historical sliding average damped engine speeds, and a plurality of historical torsional stiffness and historical damping coefficients. The database 113 is updated at predefined time intervals. These updates relate to the plurality of historical engine speeds and associated historical vehicle speed, the plurality of historical sliding average damped engine speeds, and the plurality of historical torsional stiffness and historical damping coefficients. As used herein, the term "historical" refers to past (i.e., historical) data.In the following, the operation of the system 105 includes two phases: (1) a training phase and (2) a real-time or test phase will be briefly explained.During the training phase, an anti-jerk controller model (not shown in FIG. 1 ) and a powertrain model (not shown in FIG. 1 ) of the system 105 are built or trained. The anti-jerk controller model and the powertrain model of the system 105 are developed by employing a least squares nonlinear technique or a neural network model. The neural network model includes machine learning techniques. The use of the non-linear least squares technique or the neural network model such as machine learning techniques enables continuous learning of parameters such as a gain of the jerk damper and a cut-off frequency of the jerk damper, and thereby provides effective control of (longitudinal) jerks or vibrations in real time and throughout the life of the vehicle 101.The model of the anti-jerk controller of the system 105 receives a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical sliding average attenuated engine speeds from one or more sources, i.e., the database 113, via a transceiver (not shown in FIG. 1 ) of the system 105. In one embodiment, the plurality of historical engine speeds additionally include engine speed variations. Thereafter, the anti-jerk controller model of the system 105 learns the relationship between the plurality of historical engine speeds, the associated historical vehicle speed, and the plurality of historical sliding average attenuated engine speeds to build itself (i.e., the anti-jerk controller model). That is, the model of the anti-jerk controller of the system 105 is trained using the plurality of historical engine speeds, the associated historical vehicle speed, and the plurality of historical moving average attenuated engine speeds to learn the relationship therebetween. Once the model of the anti-jerk controller of system 105 has learned the relationship between the plurality of historical engine speeds and the associated historical vehicle speed and the plurality of historical sliding average attenuated engine speeds, the model of the anti-jerk controller of system 105 is able to determine a jerk damper gain and a jerk damper cut-off frequency during the test phase.The powertrain model of the system 105 receives a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources, i.e., the database 113, via the transceiver (not shown in FIG. 1 ) of the system 105. Thereafter, the powertrain model of the system 105 learns the relationship between the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and historical damping coefficients to build itself (i.e., the powertrain model). That is, the powertrain model of the system 105 is trained using the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and damping coefficients to learn the relationship therebetween. Once the powertrain model of the system 105 has learned the relationship between the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and historical damping coefficients, the powertrain model of the system 105 is capable of updating itself (i.e., the powertrain model) to mimic the real-world powertrain of the vehicle 101 based on at least one of the vehicle speed, the engine speed, and / or the moving average damped engine speed of the vehicle 101 (i.e., making the powertrain model realistic for a current powertrain of the vehicle 101) to obtain engine speed oscillations during the test phase. Here, the real powertrain of the vehicle 101 refers to the current or actual powertrain of the vehicle 101.Once the anti-jerk controller model and the powertrain model of the system 105 are created or trained, the system 105 is operated in real-time or for testing purposes.During the real-time or test phase, the transceiver of the system 105 receives from the vehicle 101 at least one of a vehicle speed, an engine speed, or a moving average attenuated engine speed of the vehicle 101. Thereafter, the powertrain model of the system 105 updates itself (i.e., the powertrain model) to mimic the real-world powertrain of the vehicle 101 based on at least one of the vehicle speed, the engine speed, and the moving average attenuated engine speed of the vehicle to obtain engine speed variations. Next, the anti-jerk controller model of the system 105 determines a jerk damper gain and a jerk damper deactivation frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed oscillations. The variable and optimized parameters such as the shock gain and the shock cut frequency are provided in real time. This approach allows any changes in a powertrain that may have accommodated during the life of the vehicle 101 to be adjusted, thereby avoiding (longitudinal) jerking or swinging and providing smooth driving or pickup. The system transceiver 105 transmits the shock absorber gain and the shock absorber cut-off frequency to the vehicle 101 engine controller to determine a damping torque. After receiving the jerk damper gain and the jerk damper cut-off frequency, the engine control device of the vehicle 101 determines a damping torque. Once the damping torque is determined by the engine control device of the vehicle 101, a monitoring module (not shown in FIG. 1 ) of the engine control device determines a maximum allowable torque based on one of the jerk damper gain, the jerk damper cut-off frequency, and the engine speed. Thereafter, the monitoring module of the engine control device continuously monitors the torque of the vehicle 101 and keeps it below the maximum allowable torque. The monitoring module prevents unintentional acceleration due to electronic or electrical faults in an electronic control unit (ECU, also called engine control device of the vehicle 101) of the vehicle 101. For example, a malfunction of the ECU (due to electronic or electrical errors) that results in improper addition or subtraction of the torque could result in unintended acceleration of the vehicle 101. This leads to safety concerns. The presence of the monitoring module of the system 105 therefore dampens any unwanted jerks or oscillations, thereby preventing any unwanted acceleration.Because the results of the real-time or test phase are continuously fed back to the training phase to improve the anti-jerk controller model and the powertrain model of the system 105, the present disclosure functions as a closed loop for adjusting parameters such as the jerk damper gain and the jerk damper shut-off frequency.FIG. 2 shows a detailed block diagram of a system for adjusting the closed loop shock absorber parameters of a vehicle, in accordance with some embodiments of the present disclosure.The system 105, in addition to the I / O interface 107 and the processor 111 described above, also includes data 201 and one or more modules 211 (also referred to as modules) that are described in detail herein. In this embodiment, the data 201 may be stored in the memory 109. The data 201 includes, for example, vehicle data 203 and other data 205.The vehicle data 203 includes or stores at least one of a vehicle speed, an engine speed, and a moving average attenuated engine speed of the vehicle 101 received from the vehicle 101.The other data 205 may store data, including temporary data and temporary files, generated by the one or more modules 211 for performing the various functions of the system 105.In this embodiment, data 201 in memory 109 is processed by one or more modules 211 present in memory 109 of system 105. In this embodiment, the one or more modules 211 are implemented as dedicated hardware units. As used herein, the term module refers to an application specific integrated circuit (ASIC), an electronic circuit, a field programmable gate array (FPGA), a programmable system on chip (PSoC), a combinational logic circuit, and / or other suitable components that provide the described functionality. In some implementations, the one or more modules 211 are communicatively coupled to the processor 111 to perform one or more functions of the system 105. The module 211, when configured with the functionality defined in the present disclosure, provides novel hardware.In one implementation, the one or more modules 211 include, but are not limited to, a transceiver 213, an anti-jerk controller model 215, and a powertrain model 217. The one or more modules 211 also include different modules 219 to perform various other functions of the system 105. In addition to the one or more modules 211 of the system 105, an engine control device of the vehicle 101 includes a monitoring module (not shown in FIG. 2 ).Transceiver 213: During the real-time phase or the test phase, transceiver 213 receives from vehicle 101 at least one of a vehicle speed, an engine speed, or a moving average attenuated engine speed of vehicle 101 and transmits a jerk damper gain and a jerk damper shut-off frequency to the engine controller of vehicle 101 to determine an attenuation torque.During the training phase, transceiver 213 receives a plurality of historical engine speeds and associated historical vehicle speeds, a plurality of historical sliding average damped engine speeds, and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources, i.e., database 113.Anti-jerk controller model 215: During the real-time phase or the test phase, the anti-jerk controller model 215 determines a jerk damper gain and a jerk damper deactivation frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed variations.During the training phase, the anti-jerk controller model 215 receives a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical, moving average attenuated engine speeds from one or more sources, i.e., database 113, via the transceiver 213. Thereafter, the anti-jerk controller model 215 learns the relationship between the plurality of historical engine speeds, the associated historical vehicle speed, and the plurality of historical sliding average attenuated engine speeds to build the anti-jerk controller model. The anti-jerk controller model 215 is developed by employing a least squares nonlinear technique or a neural network model. The neural network model includes machine learning techniques.Powertrain Model 217: During the real-time phase or the test phase, the powertrain model 217 updates the powertrain model 217 to mimic the real (also referred to as currently) powertrain of the vehicle based on at least one of the vehicle speed, the engine speed, and / or the moving average attenuated engine speed of the vehicle to obtain engine speed variations.During the training phase, the powertrain model 217 receives a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources, i.e., database 113, via transceiver 213. Thereafter, the powertrain model 217 learns the relationship between the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and historical damping coefficients to build the powertrain model. The powertrain model 217 is developed by employing a least squares nonlinear technique or a neural network model. The neural network model includes machine learning techniques.Monitoring module: During the real-time phase or the test phase, the monitoring module determines a maximum allowable torque based on at least one of the shock absorber gain, the shock absorber cut-off frequency, and the engine speed. Thereafter, the monitoring module maintains the torque of the vehicle 101 below the maximum allowable torque. The monitoring module of the engine control device of the vehicle 101 may also be referred to as a monitoring function.FIG. 3 illustrates a flow chart illustrating a method for adjusting the closed loop shock absorber parameters of a vehicle in accordance with some embodiments of the present disclosure.As illustrated in FIG. 3, the method 300 includes one or more blocks for adjusting the vehicle closed-loop shock absorber parameters. The method 300 may be described generally in the context of computer-executable instructions. In general, computer-executable instructions may include routines, programs, objects, components, data structures, policies, entities, and functions that execute functions or implement abstract data types.The order in which method 300 is described is not intended to be limiting, and any number of the described method blocks may be combined in any order to implement the method. Moreover, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. In addition, the method may be implemented in any suitable hardware, software, firmware, or combination thereof.In block 301, the transceiver 213 of the system 105 receives at least one of a vehicle speed, an engine speed, and a moving average attenuated engine speed of the vehicle 101.At block 303, the powertrain model 217 of the system 105 updates the powertrain model 217 to mimic the real-world powertrain of the vehicle based on at least one of the vehicle speed, the engine speed, and the moving average attenuated engine speed of the vehicle to obtain engine speed variations. The powertrain model 217 is developed by employing a least squares nonlinear technique or a neural network model.At block 305, the anti-jerk controller model 215 of the system 105 determines a jerk damper gain and a jerk damper deactivation frequency based on at least one of the vehicle speed, the engine speed, the moving average damped engine speed, and the engine speed oscillations. The anti-jerk controller model 215 is developed by employing a least squares nonlinear technique or a neural network model.In block 307, the transceiver 213 of the system 105 transmits the bumper gain and the bumper cut-off frequency to an engine control device of the vehicle 101 to determine a damping torque.At block 309, the monitoring module of the vehicle 101 engine control device determines a maximum allowable torque based on at least one of the shock absorber gain, the shock absorber cut-off frequency, and the engine speed.In block 311, the monitoring module of the engine control device of the vehicle 101 maintains a torque of the vehicle 101 below the maximum allowable torque.Some of the advantages of the present disclosure are set forth below.In the present disclosure, the variable and optimized parameters such as a jerk damper gain and a jerk damper shut-off frequency are provided in real time. This approach allows any changes in a powertrain that might have accommodated during the life of a vehicle to be adjusted, thereby avoiding (longitudinal) jerking or swinging and providing smooth driving or pickup.In the present disclosure, the monitoring module prevents unintentional acceleration due to electronic or electrical faults in an electronic control unit (ECU) of a vehicle. For example, a malfunction of the ECU (due to electronic or electrical errors) that results in improper addition or subtraction of the torque could result in unintended acceleration of a vehicle. This leads to safety concerns. The presence of the monitoring module of the present disclosure therefore dampens any unwanted jerks or oscillations, thereby preventing any unwanted acceleration.In the present disclosure, using the least squares nonlinear technique or a neural network model such as machine learning techniques enables continuous learning of parameters such as a gain of the jerk damper and a shut-off frequency of the jerk damper, and thereby, effective control of (longitudinal) jerks or vibrations is provided in real time and throughout the life of a vehicle.FIG. 4 illustrates a block diagram of an example computer system 400 for implementing embodiments consistent with the present disclosure. In one embodiment, computer system 400 may be used to implement system 105. The computer system 400 may include a central processing unit ("CPU" or "processor") 402. The processor 402 may include at least one data processor for adjusting shock absorber parameters in a vehicle. The processor 402 may include specialized processing units, such as integrated system (bus) controllers, memory management controllers, floating point units, graphics processing units, digital signal processing units, etc.Processor 402 may communicate with one or more input / output (E-A) devices (not shown in FIG. 4 ) via E-A interface 401. The E-A interface 401 employs communication protocols / methods such as, without limitation, audio, analog, digital, monaural, Radio Corporation of America (RCA) connectors, stereo, IEEE® 1394 high speed serial bus, serial bus, universal serial bus (USB), infrared, personal system / 2 (PS / 2) port, bayonet neill-concelman (BNC) port, coaxial, component, composite digital visual interface (DVI), high definition multimedia interface (HDMI®), radio frequency (RF) antennas, S-video, Video graphics array (VGA), IEEE® 802.11b / g / n / x, Bluetooth, cellular, for example, code division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM®), long-term evolution (LTE®), worldwide interoperability for microwave access (WiMax®), or the like.Using the E-A interface 401, the computer system 400 may communicate with one or more E-A devices such as input devices 412 and output devices 413. The input devices 412 may be, for example, an antenna, a keyboard, a mouse, a joystick, an (infrared) keyboard, a camera, a card reader, a facsimile machine, a dongle, a biometric reader, a microphone, a touch screen, a touchpad, a trackball, a pen, a scanner, a storage device, a transceiver, a video device / source, etc. The output devices 413 may be a printer, a facsimile machine, a video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light emitting diode (LED), plasma, plasma display (PDP), organic light emitting diode display (OLED), or the like), a speaker, etc.In some embodiments, computer system 400 consists of system 105. The processor 402 may be disposed in communication with the communication network 103 and an engine control device (not shown in FIG. 4 ) of the vehicle 101 via a network interface 403. The network interface 403 may communicate with the communication network 103. The network interface 403 may employ connection protocols including, without limitation, direct connection, Ethernet (e.g., twisted pair 10 / 100 / 1000 Base T), transmission control protocol / Internet protocol (TCP / IP), token ring, IEEE® 802.11a / b / g / n / x, etc. The communication network 103 may include, without limitation, a direct connection, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using wireless application protocol), the Internet, etc. Via the network interface 403 and the communication network 103, the computer system 400 may communicate with the database 113 and the engine control device of the vehicle 101. The network interface 403 may employ connection protocols including, but not limited to, direct connection, Ethernet (e.g., twisted pair 10 / 100 / 1000 base T), transmission control protocol / internet protocol (TCP / IP), token ring, IEEE® 802.11a / b / g / n / x, etc.The communication network 103 includes, but is not limited to, a direct connection, a peer-to-peer (P2P) network, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using wireless application protocol), the Internet, Wi-Fi, and the like.In some embodiments, processor 402 may be in communication with memory 405 (e.g., RAM, ROM, etc., not shown in FIG. 4 ) via memory interface 404. The memory interface 404 may be connected to the memory 405 including, without limitation, memory drives, removable disk drives, etc., which employ connection protocols such as serial advanced technology attachment (SATA), integrated drive electronics (IDE), IEEE®- 1394, universal serial bus (USB), fiber channel, small computer systems interface (SCSI), etc. The storage drives may further include a drum, a magnetic disk drive, a magneto-optical drive, an optical drive, a redundant array of independent disks (RAID), solid state storage devices, solid state drives, etc.The memory 405 may store a collection of program or database components including, without limitation, the user interface 406, an operating system 407, etc. In some embodiments, the computer system 400 may store user / application data, such as the data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault tolerant, relational, scalable, secure databases such as Oracle or Sybase.Operating system 407 may facilitate resource management and operation of computer system 400. Examples of operating systems include, without limitation, APPLE ® MACINTOSH ® OS X ®, UNIX ®, UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTION ®( BSD), FREEBSD ®, NETBSD ®, OPENBSD, etc.), LINUX ® DISTRIBUTIONS (E.G., RED HAT ®, UBUNTU ®, KUBUNTU®, etc.), IBM®OS / 2®, MICROSOFT®WINDS®(XP®, VISTA® / 7 / 8, 10 etc.), APPLE ® IOS ®, GOOGLETM ANDROIDTM, BLACKBERRY ® OS, or the like.In some embodiments, computer system 400 may implement the program component stored in web browser 408. The web browser 408 may be a hypertext view application such as MICROSOFT ® INTERNET EXPLORER ®, GOOGLE™ CHROME™ MOZILLA ® FIREFOX ®, APPLE ® SAFARI ® etc. Secure browsing in the network may be provided using Hypertext Transport Protocol (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), etc. Web browsers 408 may utilize devices such as AJAX, DHTML, ADOBE ® FLASH ®, JAVASCRIPT ®, JAVA ®, Application Programming Interfaces (APIs), etc. The computer system 400 may implement a program component stored in a mail server (not shown in FIG. 4 ). The mail server may be an Internet mail server such as Microsoft Exchange or the like. The mail server may use devices such as ASP, ACTIVEX ®, ANSI ® C++ / C#, MICROSOFT ®,. NET, CGI SCRIPTS, JAVA ®, JAVASCRIPT ®, PERL ®, PHP, PYTHON ®, WEB OBJECTS ® etc. The mail server may use communication protocols such as Internet Message Access Protocol (IMAPP), Messaging Application Programming Interface (MAPI), MICROSOFT ® Exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. The computer system 400 may implement a program component stored in a mail client (not shown in FIG. 4 ). The mail client may be a mail view application such as APPLE ® MAIL, MICROSOFT ® INSTRUCTION ®, MICROSOFT ® OUTLOOK ®, MOZILLA ® THUNDERBIRD ® and so forth.Moreover, one or more computer readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer readable storage medium may store instructions for execution by one or more processors, including instructions to cause the processor(s) to perform steps or steps in accordance with the embodiments described herein. The term "computer readable medium" should be understood to include tangible articles and to exclude, i.e., be non-transitory, carrier waves and transient signals. Examples include random access memory (RAM), read only memory (ROM), volatile memory, non-volatile memory, hard disks, compact disks (CD) ROMs, DVDs, flash drives, floppy disks, and any other known physical storage media.The described operations may be implemented as a method, system, or article of manufacture using standard programming and / or engineering science techniques for the manufacture of software, firmware, hardware, or any combination thereof. The described operations may be implemented as code stored on a "non-transitory computer readable medium," where a processor may read and execute the code from the computer readable medium. The processor is at least one of a microprocessor and a processor capable of processing and executing the queries. A non-transitory computer readable medium may include media such as magnetic storage media (e.g., hard disks, floppy disks, tapes, and the like), optical memories (CD-ROMs, DVDs, optical disks, and the like), volatile and nonvolatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, flash memory, firmware, programmable logic, and the like), and the like. Moreover, non-transitory computer readable media includes any computer readable media other than transitory media. The code implementing the described operations may also be implemented in hardware logic (e.g., an integrated circuit chip, a programmable gate array (PGA), an application specific integrated circuit (ASIC), etc.).Moreover, the code implementing the described operations may be implemented in "transmission signals", wherein the transmission signals may propagate through space or through a transmission medium such as an optical fiber, a copper wire, or the like. The transmission signals in which the code or logic is encoded may further include a wireless signal, satellite transmission, radio waves, infrared signals, Bluetooth, and the like. The transmit signals in which the code or logic is encoded are capable of being transmitted by a transmit station and received by a receive station, wherein the code or logic encoded in the transmit signal can be decoded and stored in hardware or a non-transitory computer readable medium in the receive and transmit stations or devices. An "article of manufacture" includes a non-transitory computer readable medium, hardware logic, and / or transmission signals into which code may be implemented. An apparatus in which the code implementing the described embodiments of operations is encoded may comprise a computer readable medium or hardware logic. Of course, those skilled in the art will appreciate that many modifications may be made to this configuration without departing from the scope of the invention and that the article of manufacture may include a suitable information carrier medium known in the art.The terms "an embodiment," "an embodiment," "embodiments," "the embodiment," "the embodiments," "one or more embodiments" mean "one or more (but not all) embodiments of the invention(s)," unless expressly stated otherwise.The terms "including", "comprising", "having", and variants thereof mean "including, but not limited to", unless expressly stated otherwise.The enumeration of items does not mean that some or all items are mutually exclusive unless expressly stated otherwise.The terms "a," "an," and "the" mean "one, one, or more" unless expressly stated otherwise.The description of an embodiment having multiple components communicating with each other does not mean that all of these components are required. Rather, a variety of optional components are described to illustrate the variety of possible embodiments of the invention.When a single device or article is described herein, it will be readily appreciated that more than one device / article (whether cooperating or not) may be used in place of a single device / article. Similarly, when more than one device or article is described herein (whether or not they cooperate), it will be readily appreciated that a single device / article may be used in place of the more than one device or article, or that a different number of devices / articles may be used in place of the specified number of devices or programs. The functionality and / or features of a device may alternatively also be embodied by one or more other devices not expressly described as having these features / functions. Other embodiments of the invention therefore need not include the device itself.The illustrated operations of FIG. 3 show certain events occurring in a particular order. In alternative embodiments, certain operations may be performed, modified, or removed in a different order. Moreover, additional steps may be added to the logic described above, which still conform to the described embodiments. Moreover, the operations described herein may occur sequentially or certain operations may be processed in parallel. Moreover, the operations may be performed by a single processing unit or by distributed processing units.Finally, the language used in the specification has been chosen primarily for readability and guidance purposes, and not to delineate or rewrite the subject matter. It is therefore intended to limit the scope of the invention not by this detailed description, but rather by all claims which are made based thereon. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention as set forth in the following claims.While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are illustrative and not restrictive, the true scope being indicated by the following claims.REFERENCE NUMERALS:100 Environment 101 Vehicle 103 Communication network 105 System 107 E-A interface 109 Memory 111 Processor 113 Database 201 Data 203 Vehicle data 205 Other data 211 Module 213 Transceiver 215 Model of anti-jerk control device 217 Powertrain model 219 Other modules 400 Computer system 401 E-A interface 402 Processor 403 Network interface 404 Memory interface 405 Memory 406 User interface 407 Operating system 408 Web browser 412 Input device 413 Output device

Claims

A method for closed loop adjustment of jerk damper parameters in a vehicle (101), the method comprising the steps of: receiving at least one of a vehicle speed, an engine speed, and a sliding average attenuated engine speed of the vehicle by a transceiver (105) of a system; updating, by a powertrain model of the system (105), the powertrain model to mimic the real powertrain of the vehicle (101) based on at least one of the vehicle speed, the engine speed, and the sliding average attenuated engine speed of the vehicle (101) to obtain engine speed variations; determining, by a model of the anti-jerk controller of the system (105), a jerk damper gain and a jerk damper shut-off frequency based on at least one of the vehicle speed, the engine speed, the sliding average attenuated engine speed, and the engine speed variations; transmitting the jerk damper gain and the jerk damper cut-off frequency through the transceiver to an engine control device of the vehicle ( 101) to determine a damping torque.The method of claim 1, further comprising: determining, by a monitoring module of the engine control device, a maximum allowable torque based on one of the shock absorber gain, the shock absorber cut-off frequency, and the engine speed; and maintaining, by the monitoring module, a torque of the vehicle (101) below the maximum allowable torque.The method of claim 1, wherein the method further comprises building the powertrain model, and the steps of building comprise: receiving a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources; and learning a relationship between the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and historical damping coefficients to build the powertrain model.The method of claim 1, wherein the method further comprises building the model of the anti-jerk controller, and the steps of building comprise: receiving a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical sliding average attenuated engine speeds from one or more sources; and learning the relationship between the plurality of historical engine speeds, the associated historical vehicle speed, and the plurality of historical sliding average attenuated engine speeds to build the model of the anti-jerk controller.The method of claim 3 or 4, wherein the powertrain model and the anti-jerk controller model are developed using a least squares nonlinear technique or a neural network model.A system (105) for closed loop adjustment of shock absorber parameters in a vehicle (101), the system (105) comprising: a processor (111); and a memory (109) communicatively coupled to the processor (111), the memory (109) storing processor executable instructions that, when executed, cause the processor (111) to: receive at least one of a vehicle speed, an engine speed, and a sliding average attenuated engine speed of the vehicle; update a powertrain model to mimic the real powertrain of the vehicle (101) based on at least one of the vehicle speed, the engine speed, and the sliding average attenuated engine speed of the vehicle (101) to obtain engine speed variations; determining a jerk damper gain and a jerk damper deactivation frequency based on at least one of the vehicle speed, the engine speed, the moving average attenuated engine speed, and the engine speed variations; and transmitting the jerk damper gain and the jerk damper deactivation frequency to an engine control device of the vehicle ( 101) to determine a damping torque.The system (105) of claim 6, wherein the engine control device is communicatively coupled to the system (105) and is configured to: determine a maximum allowable torque based on at least one of the shock absorber gain, the shock absorber cut-off frequency, and the engine speed; and maintain a torque of the vehicle (101) below the maximum allowable torque.The system (105) of claim 6, wherein the processor (111) is configured to build a powertrain model to: receive a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical torsional stiffness and historical damping coefficients from one or more sources; and learn a relationship between the plurality of historical engine speeds and the corresponding historical vehicle speed and the plurality of historical torsional stiffness and historical damping coefficients to build the powertrain model.The system (105) of claim 6, wherein the processor (111) is configured to build a model of the anti-jerk controller to: receive a plurality of historical engine speeds and associated historical vehicle speeds and a plurality of historical sliding average attenuated engine speeds from one or more sources; and learn the relationship between the plurality of historical engine speeds, the associated historical vehicle speed, and the plurality of historical sliding average attenuated engine speeds to build the model of the anti-jerk controller.The system (105) of claim 8 or 9, wherein the powertrain model and the anti-jerk controller model are developed using a least squares nonlinear technique or a neural network model.

Images