FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION (See section 10, rule 13)
“A SYSTEM AND METHOD FOR PREDICTING END OF SERVICE LIFE OF CRITICAL COMPONENTS OF A VEHICLE”
MINDA CORPORATION LIMITED, of E-5/2, Chakan Industrial Area, Phase-III, M.I.D.C., Nanekarwadi, Tal: Khed, Dist.Pune-410 501, Maharashtra India
The following specification particularly describes the invention and the manner in which it is to be performed.

FIELD OF THE PRSENT INVENTION
[001] The present disclosure relates to a prognostic based predictive maintenance for predicting end of service life of critical components within the vehicle and is particularly related with methods for performing prognostic based predictive maintenance using a Smart Junction Box.
BACKGROUND OF THE PRESENT INVENTION
[002] Vehicle running time is getting increasingly crucial, especially for the commercial vehicles, which generally covers long span of distance and prefers to run on a continual basis. At the same time the transport solutions are tending to become more complex and the vehicles used in transport industry seeks new ways of providing affordable transport solutions at the suboptimal costs. Vehicles have complex structure that involves interaction among various interconnected units, each unit comprised of numerous components acting together. In order to maintain lasting hours of working, an effective maintenance strategy is highly recommended to ensure vehicle uptime and increased operational efficiency, and to help control costs.
[003] Presently, there are three types of maintenance strategies running around in vehicle industry, namely reactive/corrective maintenance, preventive maintenance and predictive maintenance. Reactive maintenance activity, which is used for infrequent failures, is a reaction to asset failure after it occurs. Reactive maintenance is the common practice in the vehicle industry, where vehicle parts are upgraded occasionally. In this strategy, the vehicle repair is deemed extremely costly. Reactive maintenance approaches are proving insufficient to deliver the desired runtime. Preventive maintenance activity takes place before something breaks, so a vehicle doesn’t incur vehicle/equipment downtime. It is almost always cheaper to do this than to wait for failure. Detailed job plans will need to be developed that spell out the maintenance tasks and the time intervals for each to keep the asset up and running. It is counted as maintenance performed on a predetermined schedule. There should also be a means to capture the conditions found at each scheduled inspection. This is usually done with a preventive maintenance work order and captured by the computerized maintenance management system (CMMS). Predictive Maintenance strategy is based on specific information about

the asset that is a reliable predictor of imminent failure, allowing maintenance to be planned before the failure occurs.
[004] At times, it is hard to diagnose failure in advance in the vehicle industry because of some design exertions. This has created opportunities for the development of smart machines that are capable of increased automation, self-monitoring and predictive diagnosis or prognosis of potential fault without human intervention. Efficient functioning of automobiles is ensured through self-monitoring and prognosis. For the same reason, the technology of providing predictive maintenance is getting more traction. Predictive maintenance technique has increased attention in many industries including the vehicle industry to provide advanced facilitation in terms of better maintenance planning, improve overall reliability as well as to increment the vehicle up¬time. In other words, in many industries inclusive of automotive vehicle industry, predictive maintenance is picking up the pace and is poised to become an integral part of service maintenance system. Predictive maintenance systems are capable of predicting the need for vehicle maintenance as well as reasonable failure of the critical components, such as head light, horn, washer/wiper etc. It uses on board diagnostics to predict and thereby prevent the occurrences of future failures.
[005] System’s current condition is evaluated by diagnostic and prognostic processes. Diagnostic protocols, including but not limited to, On Board Diagnostic protocol (OBD 2) and Unified Diagnostic Services (UDS) are used to communicate with an Electronic Control Unit (ECU). OBD2 characterizes vehicle’s self-indicative and reporting ability. On-Board Diagnostic (OBD) framework gives the vehicle owner or a repair professional access to condition of current data of different vehicle subsystems. UDS protocol will also be used to provide all the details. Diagnostics is concerned with current state of any subsystem whereas prognostic is related to the future state of subsystem.
[006] Some of the elegant smart junction box based predictive maintenance solutions are suggested in prior art. One of the prior art cites serious challenges while dealing with prognostic maintenance. Prognostic maintenance copes with onboard data. Development cost of on-board diagnostic is limited in vehicle, which results in limited

number of sensors. These sensors produce thousands of signals or data streams when vehicle is on the move. These signals are continuously sent to mobile or laptop attached with vehicle via wireless communication. It needs huge storage capacity which results in high cost. Therefore, such systems are costlier to implement across the vehicle fleet service stations.
[007] One of the other prior art combined sensor fusion, connected vehicle technology and machine learning combined with cloud computing to provide prognosis for connected cars. However, being sensor- based solution, it could not be able to diagnose end of life conditions for headlamps, wiper motors, horns etc. since these components work on a stand- alone basis and are generally not associated with any sensors. At the same time, it incurs significant cost by the provision of telematics based connected vehicle technology clubbed with intensive machine learning algorithms for prediction of health of components and thus preventing them to shut off in the real time. So, such systems though facilitative and predictive in nature, are much costlier and more complex in implementation.
[008] Therefore, there is a need of art to build an improved, cost-effective and widely adopted prognosis-based system and method thereof as an integral part of periodic vehicle monitoring and servicing which overcomes all the above-mentioned difficulties or drawbacks of disadvantages of prior arts mentioned above.
SUMMARY OF THE PRESENT INVENTION
[009] The present disclosure overcomes one or more shortcomings of the prior art and provides additional advantages discussed throughout the present disclosure. Additional features and advantages are realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.
[010] The present disclosure presents the smart junction box based predictive vehicle maintenance solution endowed with a prognosis-based feature. It proposes an improved prognosis-based system and method thereof that utilizes and implements a smart junction box based solution aimed at predicting and indicating the life of the

critical components to avoid real time failure.
[011] In one non-limiting embodiment of the present disclosure, a method for predicting end of service life of critical components of a vehicle is disclosed. The method comprising: monitoring an operation of the at least one critical component of the vehicle; maintaining a record of pre-set values of life determining parameters of at least one critical component. The life determining parameters comprises at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters of the at least one critical component as prescribed in a supplier’s specifications, during monitoring. The method further comprises of determining actual values of the life determining parameters of the at least one critical component based on monitoring; continually determining a remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values; continually comparing the remaining lifetime of the at least one critical component with a predetermined threshold to determine if the remaining lifetime of the at least one critical component is equal to or lower than the predetermined threshold; and predicting the end of service life of at least one critical component based on the comparison.
[012] In still another non-limiting embodiment of the present disclosure, the method discloses storing a result of prediction in a memory of a smart junction box of the vehicle.
[013] In still another non-limiting embodiment of the present disclosure, the method discloses wherein maintaining a record of the pre-set values of life determining parameters of the at least one critical component further comprises of: extracting data for the total operating hours, the total number of operations and the predetermined operational and technical parameters from component datasheets in the supplier’s specifications; and storing the extracted data in the memory of the smart junction box of the vehicle.
[014] In yet another non-limiting embodiment of the present disclosure, the method discloses continually comparing the remaining lifetime of the at least one critical component with the predetermined threshold further comprising: determining if the

remaining lifetime of the at least one critical component is greater than the predetermined threshold; monitoring the operation of the at least one critical component of the vehicle; and continually determine the remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold.
[015] In still another non-limiting embodiment of the present disclosure, the method discloses receiving a request to obtain the result of prediction, from a diagnostic tool during a periodic servicing visit of the vehicle; and transmitting the result of prediction to the diagnostic tool.
[016] In another non-limiting embodiment of the present disclosure, a system for predicting end of service life of critical components of a vehicle is disclosed. The system comprises of: one or more critical components; and a smart junction box in communication with the one or more critical components. The smart junction box comprises of a controller configured to monitor an operation of the at least one critical component of the vehicle; maintain a record of pre-set values of life determining parameters of at least one critical component, wherein the life determining parameters comprises at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters of the at least one critical component as prescribed in a supplier’s specifications, during monitoring; determine actual values of the life determining parameters of the at least one critical component based on monitoring, continually determine a remaining lifetime of the at least one critical component based on the difference between preset values and the actual values; continually compare the remaining lifetime of the at least one critical component with a predetermined threshold to determine if the remaining lifetime of the at least one critical component is equal to or lower than the predetermined threshold; and predict the end of service life of at least one critical component based on the comparison.
[017] In yet another non-limiting embodiment of the present disclosure, the system discloses wherein the controller is further configured to store a result of prediction in a memory of the smart junction box.

[018] In yet another non-limiting embodiment of the present disclosure, the system discloses wherein the controller when maintaining a record of the pre-set values of life determining parameters of the at least one critical component, further configured to: extract data for the total operating hours, the total number of operations and the predetermined operational and technical parameters from component datasheets in the supplier’s specifications; and storing the extracted data in the memory of the smart junction box.
[019] In still another non-limiting embodiment of the present disclosure, the system discloses wherein the controller when continually comparing the remaining lifetime of the at least one critical component with the predetermined threshold, further configured to: determine if total number of operations and the predetermined operational and technical parameters lifetime of the at least one critical component is greater than the predetermined threshold; monitor the operation of the at least one critical component of the vehicle; and continually determine the remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold.
[020] In still another non-limiting embodiment of the present disclosure, the system discloses wherein the controller is further configured to: receive a request to obtain the result of prediction, from a diagnostic tool during a periodic servicing visit of the vehicle; and transmit the result of prediction to the diagnostic tool.
[021] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments and features will become apparent by reference to the drawings and the following detailed description.
OBJECTS OF THE INVENTION
[022] The main object of the present disclosure is to determine a prognosis-based solution to predict end of life of critical components of a vehicle using smart junction

box and thus prevent the futuristic failures.
[023] Another object of the present disclosure is to alert the vehicle owner about the completion or near to completion life of critical components at the time of periodic servicing at the service station.
[024] Yet another object of the present disclosure is to avoid sudden failure of the critical components that can lead to hurtful down time, in particular, for commercial vehicles, leading to loss of business due to operational break down.
EFFECTS/ADVANTAGES OF THE PRESENT INVENTION
[025] The present disclosure offers a simple, elegant and an improved prognosis based system, in terms of zero hardware cost and a minimal software cost feature added to a smart junction box, without the inclusion of any sensors or telematics connectivity and the complex machine learning algorithms. The present disclosure takes account of supplier's life related technical guarantees prescribed in the official datasheet such as total number of operating hours, total number of operations and predetermined operational and technical parameters for head lamps, washer/wiper, fuel pump, horn, wiper control, starter motor, blower motor, A/C compressor, battery etc. and stores them in the memory for the periodic monitoring and indications on the diagnostic tool. Thus, the present disclosure presents prudent and innovative prognosis based predictive maintenance strategy incorporating a smart junction box and diagnostic tool, to avoid accidents, damage to a vehicle. The present disclosure is novel and inventive in terms of not incurring any extra hardware resource/cost and offers minimal software overhead.
[026] Other related advantages of the present disclosure are reduced weight and packaging size of the proposed system.
BRIEF DESCRIPTION OF DRAWINGS:
[027] 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 embodiments. In the figures, the left-most digit(s) of a

reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:
[028] FIG. 1 illustrates a block diagram of an environment indicating an interaction between a system for predicting end of service life of critical components of a vehicle and a service diagnostics tool, according to an embodiment of the present disclosure.
[029] FIG. 2 illustrates a block diagram of a system for predicting end of service life of critical components of a vehicle, according to an embodiment of the present disclosure.
[030] FIG. 3 discloses a flowchart of a method for predicting end of service life of critical components of a vehicle, according to an embodiment of present disclosure.
[031] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter.
DETAILED DESCRIPTION OF THE PRESENT INVENTION
[032] Referring now to the drawings, there is shown an illustrative embodiment of the disclosure “A system and method for predicting end of service life of critical components of a vehicle”. It is understood that the disclosure is susceptible to various modifications and alternative forms; specific embodiments thereof have been shown by way of example in the drawings and will be described in detail below. It will be appreciated as the description proceeds that the disclosure may be realized in different embodiments.
[033] In 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.
[034] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings 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 to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.
[035] The terms “comprises”, “comprising”, “include(s)”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, system or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.
[036] According to an aspect of the present disclosure, a technique for predicting end of service life of critical components of a vehicle is proposed which uses a smart junction box to collect prognosis related data. A vehicle may contain various components, including critical ones such as head- lamps, washer/wiper, fuel pump, horn, wiper control, starter motor, blower motor, A/C compressor, battery etc., to maintain the vehicle at the top performance and to ensure safety and convenience of the owner. The critical components of the vehicle have a prescribed life in terms of certain life determining parameters which are set by its manufacturer. In one of the non-limiting examples, these life determining parameters comprises at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters. Sudden failure of such critical components can lead to unavoidable circumstances such as accidents and other related issues which may put a vehicle owner under loss. In case of commercial vehicles, it may also lead to loss of business due to operational break down. The technique is aimed at not only driving the critical

components but at the same time monitoring information related to their operating hours, predicting, and indicating the life of the aforementioned critical components.
[037] According to another aspect of the present disclosure, during periodic
servicing a service diagnostic tool which is kept by a service technician, will communicate with the smart junction box and read the prognostic related data. The service technician can proactively alert the vehicle owner regarding those components nearing their service life before next servicing is due.
[038] Since, in the present disclosure, the smart junction box integrates passive junction box features with electronic module functionality, it uses a microcontroller to switch power and control various vehicle body functions. The present disclosure utilizes a total systems approach by optimizing and integrating control and power distribution functions into a single module.
[039] In non-limiting example, the present disclosure using smart junction box provides an off-the-shelf solution and condense system footprint for faster project execution and reduced installation costs. Smart junction box, based on intelligent microcontroller-based logic, is replacing traditional relay fuse box based electrical system architecture for vehicle. The smart junction box-based solution is a retrofit concept of replacing the mechanical relays with Intelligent Power device/driver without disturbing the wiring harness present in the vehicle. This approach makes it feasible to plug-in the solution for faster evaluation in a real time environment.
[040] According to another aspect of the present invention, the smart junction box integrates passive junction box features with electronic module functionality. It uses a microcontroller to switch power and control vehicle body functions. SJB technology utilizes a total systems approach by optimizing and integrating control and power distribution functions into a single module. These self-protecting devices improve quality and eliminate the need of serviceable fuses and relays. It reduces weight and packaging size.

[041] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and are shown by way of illustration of 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 taken in a limiting sense.
[042] FIG. 1 shows a block diagram of an environment 100 indicating an interaction between a system 101 for predicting end of service life of critical components of a vehicle and a service diagnostics tool 102 according to an embodiment of the present disclosure.
[043] In an exemplary embodiment, the system 101 comprises a smart junction box 101a and a plurality of critical components or loads 101b of a vehicle 103. As shown in the figure, the system 101 may reside inside the vehicle 103. The smart junction box 101a may be configured to drive the critical components / loads 101b, monitor and store operating hours/running distance of said components whose service life is prescribed at least in terms of number of operating hours/running distance and other operating conditions. Based on said monitoring, the smart junction box 101a predicts and indicates the life or end of service life of the critical components and stores the same in its memory. Data relating to the monitoring of the critical components in terms of number of operating hours/running distance, may be referred herein as prognostic related data. In a non- limiting example, a vehicle owner may take his/her vehicle to a workshop/ service station for periodic servicing. During the periodic servicing, the service diagnostic tool 102 which is kept by a service technician, will communicate with the system 101 and read the prognostic related data. The service technician can proactively alert the vehicle owner regarding those components nearing their service life before next servicing is due. Being informed, the vehicle owner may arrive at a decision about pro-actively replacing the potential component whose end of service life is nearing. After getting instruction from the vehicle owner, as and when desired, the service technician can replace the potential component(s) with the novel component (s), store the renewed service life/operating hours into the memory of smart junction box 101a by resetting data count for prognostics related data to zero for fresh monitoring.

[044] The detailed explanation of the system 101 for predicting end of service life of critical components of a vehicle is provided below in FIG. 2.
[045] FIG. 2 shows a block diagram of a system 200 (system 101 of FIG. 1) predicting the end of service life of the critical components of the vehicle, in accordance with an embodiment of the present disclosure.
[046] In an exemplary embodiment, the system 200 may comprise a smart junction box 200A, load/critical components 200B, a body control module 207, and different switches such as belt switch 208, door switch 209, LED switch 210, and trunk switch 211. The smart junction box 200A acts as an interface between the load/critical components 200B, the different switches and the body control module 207.
[047] In an exemplary embodiment, the smart junction box 200A may comprise a linear regulator 201, an enable switch circuit 202, multiple switch detection interface 203, a controller area network (CAN) / local interconnect network (LIN) transceiver 204, a microcontroller 205, intelligent power switch 206 and a memory 212. The linear regulator 201 may maintain a constant voltage output (VDD) to be supplied to the microcontroller 205 from the battery. When the vehicle is in “ignition” mode, the enable switch circuit 202 may control the current/voltage to the load/critical components 200B through the intelligent power switch 206. The multiple switch detection interface 203 may detect the operation of the different switches and may communicate the same to the corresponding I/O pins of the microcontroller 205. The body control module 207 is connected to the microcontroller 205 through the CAN/LIN transceiver 204.
[048] In a non-limiting example, the microcontroller 205 may communicate with the body control module 207 via CAN/LIN communication as required. The intelligent power switch 206 may provide various diagnostic and failure detection features that allow to reliably provide power to different types of loads such as load/critical components 200B. In a non-limiting example, the intelligent power switch 206 may provide overcurrent protection, short circuit protection, thermal shutdown, open load detection, and the ability to dissipate the demagnetization energy stored in an inductive

load. These protection functions can minimize the risk and severity of failures even in the event of a processing unit malfunction.
[049] The memory 212 is communicatively coupled to the microcontroller 205. In a non-limiting example, memory 212 may be an external memory chip, as a part of a smart junction box 200A component or an inbuilt EEPROM memory, within microcontroller 205. In an embodiment, the memory 212 may be a computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or synchronous dynamic random-access memory (SDRAM) and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
[050] In an embodiment, the data/information may be stored within the memory 212 in the form of various data structures. As also indicated in earlier paragraphs, the information is the prognostic related data such as working hours/running distance and other operating conditions, etc. of the critical components 200B at the time of the component installation and the data which is being stored based on monitoring of said components. In another non-limiting example, the information may include data regarding allowed number of rotations for a wiper motor. The status of battery charge and in turn the battery life in number of hours / minutes could also be stored by the connection of battery sensor on the LIN interface. The data for computing the overall life could be extracted from the component datasheets and accordingly act as an input to the memory 212. The memory 212 may also store other data such as temporary data and temporary files, generated by the various units 201-206 for performing the various functions of the smart junction box 200A.
[051] While the components 201-212 are illustrated and described herein with respect to the smart junction box 200A may form essential components to carry out the present disclosure, it may be worth noted that the smart junction box 200A may comprise other/additional components as well which are not shown for the sake of brevity and are used in conjunction with the illustrated components to implement present disclosure.

[052] According to an aspect of the present disclosure, the microcontroller 205 may be configured to monitor and continually compute the lifetime of the load/critical components 200B.
[053] In a non-limiting example, microcontroller 205 may be configured to monitor an operation of the at least one critical component 200B of the vehicle and may maintain a record of pre-set values of life determining parameters of at least one critical component 200B, during the monitoring. The life determining parameters may comprise but not limited thereto, at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters or conditions of the at least one critical component as prescribed in the supplier’s specifications. The life determining parameters for predicting end of service life may be selected depending on the type of the critical component 200B. For example, the life determining parameters for predicting end of service life for a wiper motor may be allowed number of rotations. In case of a battery, the life determining parameters for predicting end of service life may be total number of hours / minutes. These are few examples given in context of some of the critical components and their life determining parameters and a person of skill would further appreciate that the vehicle 103 may include other critical components 200B as well such as head- lamps, washer/wiper, fuel pump, horn, wiper control, starter motor, blower motor, A/C compressor, battery etc. Each of these critical components may have same or different life determining parameters or a combination of at least one of total number of operating hours, total number of operations and predetermined operating and technical parameters/conditions as prescribed in the supplier’s specifications. To maintain the record of the pre-set values of life determining parameters of the at least one critical component 200B, the microcontroller 205 may extract data for the total operating hours, the total number of operations and the predetermined operational and technical parameters/conditions from component datasheets in the supplier’s specifications and may store the extracted data in the memory 212 of the smart junction box 200A.
[054] The microcontroller 205 may determine actual values of the life determining parameters of the at least one critical component 200B based on the monitoring process and may continually determine a remaining lifetime of the at least one critical component 200B based on the difference between preset values and the actual values. In a non-

limiting example, the actual values of the life determining parameters may indicate consumed total number of operating hours, total number of operations, at a certain point of time, when a certain critical component is operating. In another non-limiting example, the actual values of the life determining parameters may indicate a value that is a measure of any deviation from the preset values or ranges of predetermined operational and technical parameters/conditions of the at least one critical component at certain point of time. The microcontroller 205 continually compare the remaining lifetime of the at least one critical component 200B with a predetermined threshold to determine if the remaining lifetime of the at least one critical component 200B is equal to or lower than the predetermined threshold; and predict the end of service life of at least one critical component 200B based on the comparison. The microcontroller 205 may store the result of prediction in the memory 212 of the smart junction box 200A.
[055] In a non-limiting example, a logic coded into the memory 212 of the smart junction box driven by the microcontroller 205 decides the predetermined threshold, such as a lower threshold of a pre-set value of at least one life determining parameter. In one example, but not limited thereto, the lower threshold may be set to e.g., before the 10 % of the component life/working hours etc., which can be made resettable by the service technician, below which the service diagnostic tool 105 starts giving warning during the periodic predictive maintenance check of the vehicle.
[056] In another non-limiting example, the microcontroller 205 may determine if the remaining lifetime of the at least one critical component 200B is greater than the predetermined threshold. If the same holds true, microcontroller 205 may continue to monitor the operation of the at least one critical component 200B of the vehicle and may continually determine the remaining lifetime of the at least one critical component 200B based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold.
[057] In another non-limiting example, the microcontroller 205 may receive a request to obtain result of prediction from a diagnostic tool 102 during a periodic servicing visit of the vehicle. The diagnostic tool 102 may be any suitable portable electronic device such as a cellphone, laptop, PDA, etc. kept by the service technician that is able communicate with the microcontroller 205 of the smart junction box 200A.

Based on the request received, the microcontroller 205 may transmit the result of prediction to the diagnostic tool 102. Based on said prediction result, the service technician may alert the vehicle owner if any of the critical components 200B is nearing its end of service life. The vehicle owner is then empowered to arrive at a judicious decision about pro-actively replacing the potential culprit component which may lead to unplanned vehicle break-down causing loss of business or other difficulties/accident due to a malfunctioning component during driving. Based on the vehicle owner’s decision, the service technician can replace the potentially culprit component and reset the prognosis related data count to zero for fresh monitoring. The present disclosure thus enables efficient functioning of automobiles through self-monitoring and prognosis.
[058] FIG. 3 discloses a flowchart of a method for predicting end of service life of the load/critical components of a vehicle, according to an embodiment of present disclosure. The method starts at block 302 by monitoring an operation of the at least one critical component of the vehicle.
[059] At block 304, the method may describe maintaining a record of pre-set values of life determining parameters of at least one critical component 200B, during the monitoring. As previously described, the life determining parameters may comprise but not limited thereto, at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters/conditions of the at least one critical component as prescribed in the supplier’s specifications. To maintain the record of the pre-set values of life determining parameters of the at least one critical component 200B, the method may describe extracting data for the total operating hours, the total number of operations and the predetermined operational and technical parameters from component datasheets in the supplier’s specifications. The method may further describe storing the extracted data in the memory 212 of the smart junction box 200A.
[060] At block 306, the method may describe determining actual values of the life determining parameters of the at least one critical component 200B based on the monitoring. Further, at block 308, the method may describe continually determining a remaining lifetime of the at least one critical component based on the difference between the pre-set values and the actual values. The actual values of the life determining

parameters may indicate a value representing total number of operating hours, total number of operations and/or is a measure of any deviation from the preset values or ranges of predetermined operational and technical parameters/conditions, at a certain point of time, measured by the microcontroller after at least one critical component 200B starts operating.
[061] At block 310, the method may describe continually comparing the remaining lifetime of the at least one critical component 200B with a predetermined threshold to determine if the remaining lifetime of the at least one critical component is equal to or lower than the predetermined threshold. As described with respect to Fig. 2, in a non-limiting example, the microcontroller 205 decides a predetermined threshold such as a lower threshold of the pre-set value of the life determining parameters. In one example, but not limited thereto, the lower threshold may be set to e.g., before the 10 % of the component life/working hours etc., below which the service diagnostic tool 105 starts giving warning during the periodic predictive maintenance check of the vehicle.
[062] At block 312, the method may describe predicting the end of service life of at least one critical component based on the comparison. The method may further describe storing the result of prediction in the memory 212 of the smart junction box 200A.
[063] In another non-limiting example, the method may describe when continually comparing the remaining lifetime of the at least one critical component with the predetermined threshold, determining if the remaining lifetime of the at least one critical component 200B is greater than the predetermined threshold. If the same holds true, the method may describe continuing the monitoring of the operation of the at least one critical component 200B of the vehicle and may continually determine the remaining lifetime of the at least one critical component 200B based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold. The method may further describe storing the result of prediction in the memory 212 of the smart junction box 200A.
[064] In another non-limiting example, the method may describe receiving a request to obtain result of prediction, from a diagnostic tool 102 kept by the service technician during a periodic servicing visit of the vehicle. Further, the method may describe

transmitting the result of prediction to the diagnostic tool 102. Based on said prediction result, the service technician may alert the vehicle owner if any of the critical components 200B is nearing its end of service life. The vehicle owner may then arrive at a decision of pro-actively replacing the potential culprit component which may lead to unplanned vehicle break-down or other difficulties/accident due to a malfunctioning critical component during driving. Based on the vehicle owner’s decision, the service technician can replace the malfunctioning critical component and reset the prognosis related data count to zero for fresh monitoring.
[065] The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed.
[066] Furthermore, 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 for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer- readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., are non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
[067] Suitable processors include, by way of example, a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs),

Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), and/or a state machine.
[068] Those of skill would further appreciate that the various illustrative blocks, units, modules and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
[069] While the present disclosure has been described by way of example and in terms of the preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments. To the contrary, it is intended to cover various modifications and similar arrangements (as would be apparent to those skilled in the art). Therefore, the scope of the appended claims should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements.
[070] Reference Numerals:

101, 200 System
101a, 200A Smart junction box
102 Service diagnostic tool
101b, 200B Load critical components
103 Vehicle
201 Linear regulator
202 Enable switch circuit 2
203 Multiple switch detection

interface
204 Cable area network (CAN) transceiver
205 Microcontroller
206 Intelligent power switch
207 Body control module
208 Belt switch
209 Door switch
210 LED switch
211 Trunk switch
212 Memory
300 Method
302-312 Method steps

WE CLAIM:
1. A method for predicting end of service life of critical components of a vehicle, the
method comprising:
monitoring an operation of the at least one critical component of the vehicle;
maintaining a record of pre-set values of life determining parameters of at least one critical component, wherein the life determining parameters comprises at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters of the at least one critical component as prescribed in a supplier’s specifications, during monitoring;
determining actual values of the life determining parameters of the at least one critical component based on monitoring;
continually determining a remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values;
continually comparing the remaining lifetime of the at least one critical component with a predetermined threshold to determine if the remaining lifetime of the at least one critical component is equal to or lower than the predetermined threshold; and
predicting the end of service life of at least one critical component based on the comparison.
2. The method as claimed in claim 1, further comprising storing a result of prediction in a memory of a smart junction box of the vehicle.
3. The method as claimed in claim 1, wherein maintaining a record of the pre-set values of life determining parameters of the at least one critical component further comprising:
extracting data for the total operating hours, the total number of operations and the predetermined operational and technical parameters from component datasheets in the supplier’s specifications; and
storing the extracted data in the memory of the smart junction box of the vehicle.
4. The method as claimed in claim 1, continually comparing the remaining lifetime of the at
least one critical component with the predetermined threshold further comprising:
determining if the remaining lifetime of the at least one critical component is greater than the predetermined threshold;

monitoring the operation of the at least one critical component of the vehicle; and continually determine the remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold.
5. The method as claimed in claim 2, further comprising:
receiving a request to obtain the result of prediction, from a diagnostic tool during a periodic servicing visit of the vehicle; and
transmitting the result of prediction to the diagnostic tool.
6. A system for predicting end of service life of critical components of a vehicle, the system
comprising:
one or more critical components; and
a smart junction box in communication with the one or more critical components, the smart junction box comprising: a controller configured to:
monitor an operation of the at least one critical component of the vehicle;
maintain a record of pre-set values of life determining parameters of at least one critical component, wherein the life determining parameters comprises at least one of total number of operating hours, total number of operations and predetermined operational and technical parameters of the at least one critical component as prescribed in a supplier’s specifications, during monitoring;
determine actual values of the life determining parameters of the at least one critical component based on monitoring,
continually determine a remaining lifetime of the at least one critical component based on the difference between preset values and the actual values;
continually compare the remaining lifetime of the at least one critical component with a predetermined threshold to determine if the remaining lifetime of the at least one critical component is equal to or lower than the predetermined threshold; and
predict the end of service life of at least one critical component based on the comparison.

7. The system as claimed in claim 6, wherein the controller is further configured to store a result of prediction in a memory of the smart junction box.
8. The system as claimed in claim 6, wherein the controller when maintaining a record of the pre-set values of life determining parameters of the at least one critical component, further configured to:
extract data for the total operating hours, the total number of operations and the predetermined operational and technical parameters from component datasheets in the supplier’s specifications; and
storing the extracted data in the memory of the smart junction box.
9. The system as claimed in claim 6, wherein the controller when continually comparing the
remaining lifetime of the at least one critical component with the predetermined
threshold, further configured to:
determine if the remaining lifetime of the at least one critical component is greater than the predetermined threshold;
monitor the operation of the at least one critical component of the vehicle; and continually determine the remaining lifetime of the at least one critical component based on the difference between the preset values and the actual values to predict the end of service life based on the comparison with the predetermined threshold.
10. The system as claimed in claim 7, wherein the controller further configured to:
receive a request to obtain the result of prediction, from a diagnostic tool during a periodic servicing visit of the vehicle; and
transmit the result of prediction to the diagnostic tool.