Abstract: A diagnostic scan tool is provided including a connect/configure module for establishing a communication link between the scan tool and a vehicle electronic control unit (ECU). A vehicle specification module operates to identify a vehicle under test in response to receipt of a vehicle identification number (VIN). A trouble code module retrieves digital trouble codes (DTCs) from the ECU. A freeze frame data module retrieves freeze frame data from the ECU, the retrieved freeze frame data being functionally associated with a highest priority DTC. A database lists possible vehicle defect solutions, indexed to the VIN and the DTCs. A digital signal processor is operative to derive the highest priority DTC from analysis of the retrieved freeze frame data. The digital signal processor further being operative to regulate selection of a most likely vehicle defect solution associated with the VIN and the highest priority DTC.

Abstract: A diagnostic scan tool is provided including a connect/configure module for establishing a communication link between the scan tool and a vehicle electronic control unit (ECU). A vehicle specification module operates to identify a vehicle under test in response to receipt of a vehicle identification number (VIN). A trouble code module receives digital trouble codes (DTCs) from the ECU. A freeze frame data module retrieves freeze frame data from the ECU, the retrieved freeze frame data being functionally associated with a highest priority DTC. A database lists possible vehicle defect solutions, indexed to the VIN and the DTCs. A digital signal processor is operative to derive the highest priority DTC from analysis of the retrieved freeze frame data. The digital signal processor further being operative to regulate selection of a most likely vehicle defect solution associated with the VIN and the highest priority DTC.

Abstract: A method is disclosed for determining the cost of operating a vehicle over a defined period of time. The method proceeds by establishing, on a database, a schedule of anticipated future repairs for a plurality of vehicle types, the repair schedule including the cost of the repairs and the approximate mileage at which the anticipated future repair(s) are expected to become necessary. A processor, in communication with the database, receives information identifying a particular of vehicle, and the present mileage associated with that particular vehicle. Using the vehicle type information, the vehicle's present mileage information and the repair schedule, the processor then computes the approximate total future repair costs for maintaining the vehicle over a defined period of time.

Abstract: There is provided a method of predicting defects likely to occur in a vehicle over a predetermined period. The method includes receiving vehicle characteristic data regarding a vehicle under consideration, and comparing the received vehicle characteristic data with a defect database. The defect database includes information related to defects that have occurred in different vehicles and the mileage at which such defects occurred. The method additionally includes identifying defects that occurred in vehicles corresponding to use vehicle under consideration, and the mileage at which such defects occurred. Detects which fail to satisfy minimum count requirements are then filtered out, and the defects are then sorted in order of the highest defect count.

Abstract: A method of processing vehicle diagnostic data is provided for identifying likely vehicle fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving vehicle diagnostic data from a vehicle onboard computer at a remote diagnostic database, the database being arranged to map vehicle diagnostic data to possible vehicle fix(s). The possible vehicle fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a vehicle repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: A diagnostic scan tool is provided including a connect/configure module for establishing a communication link between the scan tool and a vehicle electronic control unit (ECU). A vehicle specification module operates to identify a vehicle under test in response to receipt of a vehicle identification number (VIN). A trouble code module receives digital trouble codes (DTCs) from the ECU. A freeze frame data module retrieves freeze frame data from the ECU, the retrieved freeze frame data being functionally associated with a highest priority DTC. A database lists possible vehicle defect solutions, indexed to the VIN and the DTCs. A digital signal processor is operative to derive the highest priority DTC from analysis of the retrieved freeze frame data. The digital signal processor further being operative to regulate selection of a most likely vehicle defect solution associated with the VIN and the highest priority DTC.

Abstract: A method of processing vehicle diagnostic data is provided for identifying likely vehicle fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving vehicle diagnostic data from a vehicle onboard computer at a remote diagnostic database, the database being arranged to map vehicle diagnostic data to possible vehicle fix(s). The possible vehicle fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a vehicle repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: A scan tool is provided which comprises a housing which houses a display and six mode buttons. The scan tool is communicable with an OBD of an automobile and provides information retrieved therefrom to a user of the scan tool in an efficient and effective manner. In particular, the display displays a plurality of information on one screen. For example, the display may display information related to I/M Monitor Status simultaneously with MIL status, stored, pending or historical codes. Further, the scan tool allows the user to switch between modes by depressing the mode button of the desired mode without having to manually exit the current mode and manually enter the desired mode.

Abstract: A method of processing system diagnostic data is provided for identifying likely device fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving diagnostic data from a system onboard computer at a remote diagnostic database, the database being arranged to map system diagnostic data to possible vehicle fix(s). The possible device fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a system repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: There is provided a method of providing vehicle support. The method includes receiving diagnostic data from the onboard vehicle computer. The diagnostic data is received by an automotive diagnostic tool and is then communicated to a prior experience database having information related to diagnostic solutions associated with combinations of diagnostic data. The prior experience database is arranged to match the received diagnostic data to possible diagnostic solutions. The diagnostic solutions are then prioritized in accordance with ranked matches of the received diagnostic data to the previous combinations of diagnostic data stored in the prior experience database. The possible diagnostic solution associated with the highest ranked combination of diagnostic data is identified as the most likely solution. Vehicle components associated with the most likely solution are then identified.

Abstract: A method of processing vehicle diagnostic data is provided for identifying likely vehicle fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving vehicle diagnostic data from a vehicle onboard computer at a remote diagnostic database, the database being arranged to map vehicle diagnostic data to possible vehicle fix(s). The possible vehicle fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a vehicle repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: A method of processing vehicle diagnostic data is provided for identifying likely vehicle fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving vehicle diagnostic data from a vehicle onboard computer at a remote diagnostic database, the database being arranged to map vehicle diagnostic data to possible vehicle fix(s). The possible vehicle fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a vehicle repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: A scan tool is provided which comprises a housing which houses a display and six mode buttons. The scan tool is communicable with an OBD of an automobile and provides information retrieved therefrom to a user of the scan tool in an efficient and effective manner. In particular, the display displays a plurality of information on one screen. For example, the display may display information related to I/M Monitor Status simultaneously with MIL status, stored, pending or historical codes. Further, the scan tool allows the user to switch between modes by depressing the mode button of the mode without having to manually exit the current mode and manually enter the mode.

Abstract: It is the object of this invention to provide a system and method in the form of a program called automotive DTC live data diagnostics for analyzing live data, in real time, wherein received and analyzed diagnostic trouble codes (DTCs) are programmed to open the live data mode, selecting only the live data related to the tests used to determine the DTCs and loads and displays all the PIDs, flagging the abnormal PIDs. The invention eliminates the necessity of manually scanning through possibly several hundred PIDs in order to determine the abnormal PIDS.

Abstract: A method of processing vehicle diagnostic data is provided for identifying likely vehicle fix(s) associated with a diagnostic data, and identifying a repair procedure(s) for correcting the likely fix(s). The process receiving vehicle diagnostic data from a vehicle onboard computer at a remote diagnostic database, the database being arranged to map vehicle diagnostic data to possible vehicle fix(s). The possible vehicle fix(s) are prioritized in accordance with ranked matches of the received diagnostic data to combinations of diagnostic data stored in a prior experience database. The prior experience database having an identified fix associated with each stored combination of diagnostic data. The fix associated with the highest ranked combination of diagnostic data is identified as the most likely fix. The most likely fix is mapped to a vehicle repair database, the most likely fix being directly mapped to an associated repair procedure for repairing the most likely fix.

Abstract: A scan tool is provided which comprises a housing which houses a display and six mode buttons. The scan tool is communicable with an OBD of an automobile and provides information retrieved therefrom to a user of the scan tool in an efficient and effective manner. In particular, the display displays a plurality of information on one screen. For example, the display may display information related to I/M Monitor Status simultaneously with MIL status, stored, pending or historical codes. Further, the scan tool allows the user to switch between modes by depressing the mode button of the desired mode without having to manually exit the current mode and manually enter the desired mode.

Abstract: There is provided a method of providing vehicle support. The method includes receiving diagnostic data from the onboard vehicle computer. The diagnostic data is received by an automotive diagnostic tool and is then communicated to a prior experience database having information related to diagnostic solutions associated with combinations of diagnostic data. The prior experience database is arranged to match the received diagnostic data to possible diagnostic solutions. The diagnostic solutions are then prioritized in accordance with ranked matches of the received diagnostic data to the previous combinations of diagnostic data stored in the prior experience database. The possible diagnostic solution associated with the highest ranked combination of diagnostic data is identified as the most likely solution. Vehicle components associated with the most likely solution are then identified.