The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Pak Kin Wong - One of the best experts on this subject based on the ideXlab platform.

  • case based adaptation for automotive engine electronic control unit calibration
    Expert Systems With Applications, 2010
    Co-Authors: Chiman Vong, Pak Kin Wong
    Abstract:

    The automotive engine performance is greatly affected by the calibration of its electronic control unit (ECU). The method for ECU calibration is traditionally done by trial-and-error. This traditional method consumes a large amount of time and money. To resolve this problem, case-based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA) (Craw, Jarmulak, & Rowe, 2001; Craw, Wiratunga, & Rowe, 2006; Leake, Kinley, & Wilson, 1996, 1997). CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.

  • case based reasoning for automotive engine electronic control unit calibration
    International Conference on Information and Automation, 2009
    Co-Authors: Chiman Vong, Pak Kin Wong, H Huang
    Abstract:

    The automotive engine performance is greatly affected by the calibration of ECU, which controls fuel injection and ignition advance over different timing. Fine tuning an engine giving maximum performance is equivalent to calibrating the ECU of that engine. However, the method for ECU calibration is traditionally done in a trial-and-error way. Every trial means an adjustment to the fuel and ignition maps and then run on a dynamometer to verify the engine performance. This traditional method expenses a large amount of time and money. In order to resolve this problem, Case-based Reasoning (CBR) from artificial intelligence field is employed so that the maps of a fully calibrated ECU can be adapted to fit another similar class of engines. This paper briefly reviews the methodology of CBR. Then the application of CBR to ECU calibration is described. By applying CBR, the efficiency of calibrating an automotive ECU becomes higher. Furthermore, expert and novice automotive engineers may use this system as an assistant when calibrating an ECU. A prototype system has been developed to verify the usefulness of CBR in ECU calibration.

Chiman Vong - One of the best experts on this subject based on the ideXlab platform.

  • case based adaptation for automotive engine electronic control unit calibration
    Expert Systems With Applications, 2010
    Co-Authors: Chiman Vong, Pak Kin Wong
    Abstract:

    The automotive engine performance is greatly affected by the calibration of its electronic control unit (ECU). The method for ECU calibration is traditionally done by trial-and-error. This traditional method consumes a large amount of time and money. To resolve this problem, case-based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA) (Craw, Jarmulak, & Rowe, 2001; Craw, Wiratunga, & Rowe, 2006; Leake, Kinley, & Wilson, 1996, 1997). CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.

  • case based reasoning for automotive engine electronic control unit calibration
    International Conference on Information and Automation, 2009
    Co-Authors: Chiman Vong, Pak Kin Wong, H Huang
    Abstract:

    The automotive engine performance is greatly affected by the calibration of ECU, which controls fuel injection and ignition advance over different timing. Fine tuning an engine giving maximum performance is equivalent to calibrating the ECU of that engine. However, the method for ECU calibration is traditionally done in a trial-and-error way. Every trial means an adjustment to the fuel and ignition maps and then run on a dynamometer to verify the engine performance. This traditional method expenses a large amount of time and money. In order to resolve this problem, Case-based Reasoning (CBR) from artificial intelligence field is employed so that the maps of a fully calibrated ECU can be adapted to fit another similar class of engines. This paper briefly reviews the methodology of CBR. Then the application of CBR to ECU calibration is described. By applying CBR, the efficiency of calibrating an automotive ECU becomes higher. Furthermore, expert and novice automotive engineers may use this system as an assistant when calibrating an ECU. A prototype system has been developed to verify the usefulness of CBR in ECU calibration.

Shunsuke Chigusa - One of the best experts on this subject based on the ideXlab platform.

  • an integrated diagnostic development process for automotive engine control systems
    Systems Man and Cybernetics, 2007
    Co-Authors: K R Pattipati, Liu Qiao, Shunsuke Chigusa
    Abstract:

    Theory and applications of model-based fault diagnosis have progressed significantly in the last four decades. In addition, there has been increased use of model-based design and testing in the automotive industry to reduce design errors, perform rapid prototyping, and hardware-in-the-loop simulation (HILS). This paper presents a new model-based diagnostic development process for automotive engine control systems. This process seamlessly employs a graph-based dependency model and mathematical models for online/offline diagnosis. The hybrid method improves the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on empirical models, enables remote diagnosis, and responds to the challenges of increased system complexity. The development platform consists of an engine electronic control unit (ECU) rapid prototyping system and HILS equipment - the air intake subsystem (AIS). The diagnostic strategy is tested and validated using the HILS platform.

Doretta Oliva - One of the best experts on this subject based on the ideXlab platform.

  • post coma persons emerged from a minimally conscious state and showing multiple disabilities learn to manage a radio listening activity
    Research in Developmental Disabilities, 2012
    Co-Authors: Giulio E Lancioni, Nirbhay N Singh, Mark F Oreilly, Jeff Sigafoos, Fabio Colonna, Francesca Buonocunto, Valentina Sacco, Marisa Megna, Doretta Oliva
    Abstract:

    This study assessed microswitch-based technology to enable three post-coma adults, who had emerged from a minimally conscious state but presented motor and communication disabilities, to operate a radio device. The material involved a modified radio device, a microprocessor-based electronic control unit, a personal microswitch, and an amplified MP3 player. The study was carried out according to a non-concurrent multiple baseline design across participants. During the intervention, all three participants learned to operate the radio device, changing stations and tuning on some of them longer amounts of time than on others (i.e., suggesting preferences among the topics covered by those stations). They also ended a number of sessions before the maximum length of time allowed for them had elapsed. The practical (rehabilitation) implications of the findings were discussed.

  • helping a man with acquired brain injury and multiple disabilities manage television use via assistive technology
    Clinical Case Studies, 2010
    Co-Authors: Giulio E Lancioni, Nirbhay N Singh, Mark F Oreilly, Jeff Sigafoos, Doretta Oliva, Mario Signorino, Marina De Tommaso
    Abstract:

    This single case study was an effort to assess a technology-based program aimed at promoting independent television use by a man with acquired brain injury and multiple disabilities. The technology’s main components were: (a) two microswitches, which allowed the man to request and confirm/trigger with small responses basic television operations (i.e., switching the television on or off and changing channels), and (b) an electronic control unit with an amplified MP3 player, which helped the man with verbal instructions and the execution of the television operations. Results showed that the technology-based program succeeded in enabling the man to manage television use independently. Different amounts of time dedicated to various television programs suggested that the man had different levels of interest for them and could choose among them.

K R Pattipati - One of the best experts on this subject based on the ideXlab platform.

  • an integrated diagnostic development process for automotive engine control systems
    Systems Man and Cybernetics, 2007
    Co-Authors: K R Pattipati, Liu Qiao, Shunsuke Chigusa
    Abstract:

    Theory and applications of model-based fault diagnosis have progressed significantly in the last four decades. In addition, there has been increased use of model-based design and testing in the automotive industry to reduce design errors, perform rapid prototyping, and hardware-in-the-loop simulation (HILS). This paper presents a new model-based diagnostic development process for automotive engine control systems. This process seamlessly employs a graph-based dependency model and mathematical models for online/offline diagnosis. The hybrid method improves the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on empirical models, enables remote diagnosis, and responds to the challenges of increased system complexity. The development platform consists of an engine electronic control unit (ECU) rapid prototyping system and HILS equipment - the air intake subsystem (AIS). The diagnostic strategy is tested and validated using the HILS platform.