Bengaluru, Karnataka, India
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I am passionate about how Technology and business shape the world around us. I have had…

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  • Bosch Global Software Technologies

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Publications

  • MVEM-Based Fault Diagnosis of Automotive Engines Using Dempster–Shafer Theory and Multiple Hypotheses Testing

    IEEE Transactions on Systems, Man, and Cybernetics: Systems (Volume: 45 , Issue: 7)

    engines exhibit fast pulsating short-time dynamics due to the reciprocating cylinder motion, around mean operating points that change comparatively slow due to inputs such as throttle and load. Comparatively, simple mean value engine models (MVEM) describe the slow changes of the averaged states for automotive control and fault diagnosis. In this paper, a bank of state estimators based on MVEMs is used for fault residual generation. Three faults: 1) throttle mass air-flow sensor fault; 2)…

    engines exhibit fast pulsating short-time dynamics due to the reciprocating cylinder motion, around mean operating points that change comparatively slow due to inputs such as throttle and load. Comparatively, simple mean value engine models (MVEM) describe the slow changes of the averaged states for automotive control and fault diagnosis. In this paper, a bank of state estimators based on MVEMs is used for fault residual generation. Three faults: 1) throttle mass air-flow sensor fault; 2) exhaust gas recirculation valve sensor fault; and 3) exhaust leak fault are considered here. These faults are significant as they affect emission levels. Optimized thresholds for residual classification are derived for minimizing false alarm rates and missed detection rates. The diagnosis logic, based on the principles of structured residuals proposed in literature, is extended here for multiple hypotheses testing. Furthermore, the Dempster-Shafer theory is used to associate a confidence measure with the decision conclusions and this is shown to improve isolation. Performance is demonstrated with automotive engine data obtained from a four-cylinder instantaneous spark-ignition engine (gasoline) system model, developed in the simulation software AMESim.

    Other authors
    • A K Deb
    • S Mukhopadhyay
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  • Development of SI-Engine based Extended MVEMs for use in Estimators for Engine Health Management

    SAE Technical Paper Series

    Mean Value Engine Models (MVEM) represent average behaviour of an engine over one or more thermodynamic cycles and have been designed for automotive control and diagnosis applications. However, most MVEMs are limited to the description of the dynamics of few engine sub-systems. The diagnostic capabilities of a vehicular engine health management (VEHM) system that uses such MVEMs are limited. In this paper, the process of deriving an MVEM for an entire engine system from an instantaneous…

    Mean Value Engine Models (MVEM) represent average behaviour of an engine over one or more thermodynamic cycles and have been designed for automotive control and diagnosis applications. However, most MVEMs are limited to the description of the dynamics of few engine sub-systems. The diagnostic capabilities of a vehicular engine health management (VEHM) system that uses such MVEMs are limited. In this paper, the process of deriving an MVEM for an entire engine system from an instantaneous within-cycle crank-angle model (WCCM) is described. This is expected to be more beneficial for fault diagnosis in VEHMs since such MVEMs in the context of state observers, can be used to detect a broader range of faults and also generate a larger number of fault signatures for better fault detection and isolation (FDI). Extended Kalman Filter (EKF) based estimators are developed that use this MVEM for state estimation. The quality of estimation results was significantly improved by modelling the inaccuracy of the MVEM as a bias and extending the MVEM with the knowledge of these bias tables. Fault residue generators are designed using various MVEM-based fault models in a state observer.

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  • Development of Extended MVEM based Fault Residue Generators using UKF state Observers

    2011 Annual IEEE India Conference (INDICON)

    Mean Value Engine Models (MVEM) are used to model the averaged dynamics of an automobile engine system for control and fault diagnosis. One approach to automobile fault diagnosis is to employ the use of a bank of residual generators each of which use a fault model and produces fault residues. These fault residues could then be used to detect or isolate faults using fault detection logic in the Fault Diagnoser. In this paper, the process of building such residue generators as Unscented Kalman…

    Mean Value Engine Models (MVEM) are used to model the averaged dynamics of an automobile engine system for control and fault diagnosis. One approach to automobile fault diagnosis is to employ the use of a bank of residual generators each of which use a fault model and produces fault residues. These fault residues could then be used to detect or isolate faults using fault detection logic in the Fault Diagnoser. In this paper, the process of building such residue generators as Unscented Kalman Filter (UKF) based state observers that use different MVEM fault models has been described. Analytical redundancy can be used to detect sensor faults and is used to estimate sensor bias in a Mass Air Flow (MAF) sensor. A new fault model to detect flows has been described and is used to estimate Exhaust Gas Recirculation (EGR) flow rates for EGR valve sensor fault detection and leak flow for exhaust manifold leak detection.

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  • Development of Extended MVEM based UKF Estimators

    2011 Annual IEEE India Conference (INDICON)

    Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers. Since the measurements could be noisy and asynchronous, they should be suitably post-processed before feeding them to a state observer. In this paper, an Unscented Kalman Filter (UKF) was developed for an Extended MVEM and a suitable…

    Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers. Since the measurements could be noisy and asynchronous, they should be suitably post-processed before feeding them to a state observer. In this paper, an Unscented Kalman Filter (UKF) was developed for an Extended MVEM and a suitable post-processing algorithm for the measurements has been described.

    Other authors
    • A K Deb
    • S Mukhopadhyay
    See publication
  • Development and Validation of an MVEM from an SI-Engine based WCCM

    Proceedings of 2011 International Conference on Modelling, Identification and Control,

    Mean Value Engine Models (MVEM) model the averaged dynamics of an automobile engine and have been used for the purpose of automotive control and fault diagnosis. Within-Cycle, Crank-Angle based Models (WCCM) are complex models that model the instantaneous dynamics of engine states and replace a real engine for simulation purposes. A WCCM was constructed on the simulation platform AMESim™. An MVEM was derived from this simulation data. The motivation for this work was to use this model in an…

    Mean Value Engine Models (MVEM) model the averaged dynamics of an automobile engine and have been used for the purpose of automotive control and fault diagnosis. Within-Cycle, Crank-Angle based Models (WCCM) are complex models that model the instantaneous dynamics of engine states and replace a real engine for simulation purposes. A WCCM was constructed on the simulation platform AMESim™. An MVEM was derived from this simulation data. The motivation for this work was to use this model in an MVEM based Fault Diagnoser.

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  • The need for Bias Modelling in MVEM based Estimators

    Proceedings of 2011 International Conference on Modelling, Identification and Control

    Mean Value Engine Models (MVEM) have been used extensively in automotive controls especially over the last 20 years. An MVEM was derived from a detailed Within-Cycle, Crank-Angle based Model (WCCM) that modelled the fluctuating cylinder combustion driven dynamics of a Spark Ignition engine. The model was designed for eventual use in a Fault Diagnoser built for an automobile engine system. While using this model in Extended Kalman Filter based estimators for fault residue generation, it was…

    Mean Value Engine Models (MVEM) have been used extensively in automotive controls especially over the last 20 years. An MVEM was derived from a detailed Within-Cycle, Crank-Angle based Model (WCCM) that modelled the fluctuating cylinder combustion driven dynamics of a Spark Ignition engine. The model was designed for eventual use in a Fault Diagnoser built for an automobile engine system. While using this model in Extended Kalman Filter based estimators for fault residue generation, it was noted that the model suffered from biases that impaired the quality of estimation results. The biases were found to originate from the inherent simplifications associated with MVEMs. This led to an understanding of the limits of accuracy of a traditional MVEM model, the need for accurate bias modelling and the development of more robust estimators. Estimation results were found to improve after bias correction using Least-Square Support Vector Regressors.

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Projects

  • Entrepreneurship workshop

    Winning business idea at TU/e's Entrepreneurship workshop. Was based on business ideas for an Android/Apple-online-store-type of 3-D printing platform where users can buy and sell designs online.

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  • Honeywell Quality Conformance (QC) program

    This involved ensuring the technical competence and compliance to specifications of products of companies who wished to purchase the Honeywell brand name.The products included CFL bulbs, Generator sets, a Water purifier and an Air Cooler System. The project involved the development of test procedures to ensure quality conformance and the running of many of these tests.

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  • Reliability analysis for Component Replacement

    This involved searching for alternate suitable electronic components from suppliers when supply for existing components in Honeywell Avionics electronic boards was stalled. This involved matching specifications of the component with those from various suppliers, contacting the suppliers and using the supplier’s test data for the component in an in-house statistical tool to determine if reliability standards were met.

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  • Technology benchmarking for a Split AC system

    The project involved applying Reverse Engineering principles for technology benchmarking in order to access the technological feasibility in getting into the Split AC market.

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  • Value Engineering Analysis for a Miniature Circuit Breaker (MCB)

    Value engineering involves the application of tools and techniques with the purpose of improving the value of a mature product, either by reducing cost and/or by increasing the functionality of the product under study. This requires innovative thinking in order to come up with business viable ideas to achieve the same. In general, the projects involve studying the product, reverse engineering the product and developing an approximate Bill of Materials (BOM) for the same with help from relevant…

    Value engineering involves the application of tools and techniques with the purpose of improving the value of a mature product, either by reducing cost and/or by increasing the functionality of the product under study. This requires innovative thinking in order to come up with business viable ideas to achieve the same. In general, the projects involve studying the product, reverse engineering the product and developing an approximate Bill of Materials (BOM) for the same with help from relevant specialists, benchmarking it with competitor products in the market, pointing out the technological differences and proposing ideas to improve the value of the product. This was done for a Miniature Circuit Breaker (MCB) that was a part of the Honeywell product portfolio.

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  • Development and deployment of a real-time HIL model of an Engine After-treatment System for diagnostics and control

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    Developed three of four modules of an in-house Exhaust After-treatment System satisfying real-time requirements and ran at 10x faster than a reference model with proven robustness;
    Provided proof of concept to reduce computational load by a further 10x. (DAF Trucks)
    Calibrated above model reducing predicted NOx emission errors by roughly 10x with respect to initial values for WHTC standard emissions cycle  Deployed above model on a Hardware-in-Loop (HIL) system and developed a live…

    Developed three of four modules of an in-house Exhaust After-treatment System satisfying real-time requirements and ran at 10x faster than a reference model with proven robustness;
    Provided proof of concept to reduce computational load by a further 10x. (DAF Trucks)
    Calibrated above model reducing predicted NOx emission errors by roughly 10x with respect to initial values for WHTC standard emissions cycle  Deployed above model on a Hardware-in-Loop (HIL) system and developed a live console for EAS monitoring and diagnostics

  • Development of a Dutch Electric Vehicle, Altramotive

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    Group Project: Vehicle dynamics and control – Development of a Dutch Electric Vehicle

    Goal: Propose powertrain configuration for a common electric vehicle platform that can be used for a passenger car, taxi and regional distribution vehicle

    Personal Contribution: Battery modelling, Battery market analysis, single track and double track models for vehicle dynamics

  • HMI design for Vulnerable Road Users Collision Avoidance

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    Group Project: Human Machine Interface – user-centred design

    Goal: To develop a tablet-based HMI that allows for demonstration of driver-adaptive functionality of specific systems: a VRU collision avoidance system and/or a cooperative AEB system. Focus is on driver acceptance of the HMI and a demonstration of the HMI and its functionality in a chosen test-case scenario.

    Personal Contribution: Java programming in the Android SDK environment, interface design considering UCD…


    Group Project: Human Machine Interface – user-centred design

    Goal: To develop a tablet-based HMI that allows for demonstration of driver-adaptive functionality of specific systems: a VRU collision avoidance system and/or a cooperative AEB system. Focus is on driver acceptance of the HMI and a demonstration of the HMI and its functionality in a chosen test-case scenario.

    Personal Contribution: Java programming in the Android SDK environment, interface design considering UCD concerns such as cognitive load and persuasion, using the DistractR toolkit to measure user distraction.

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  • TNO's Intelligent Vehicle Safety Platform

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    Group Project: Development of an intelligent vehicle safety platform (iVSP) - Software platform for next generation cooperative ADAS development

    Goal: Develop and implement a layer-based software platform – Overall Architecture, Interface and Subscription layer, Sensor and Communication layer, Information layer and Application layer. Demonstrate the same on three cooperative examples – red light violation warning, in-vehicle safety event detection and offline unsafe event presentation…

    Group Project: Development of an intelligent vehicle safety platform (iVSP) - Software platform for next generation cooperative ADAS development

    Goal: Develop and implement a layer-based software platform – Overall Architecture, Interface and Subscription layer, Sensor and Communication layer, Information layer and Application layer. Demonstrate the same on three cooperative examples – red light violation warning, in-vehicle safety event detection and offline unsafe event presentation.

    Personal Contribution: Software System Architecture and Design in SysML, Development of Use-case scenarios, setting requirements between different software layers

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  • In-wheel driving module for electric VW Lupo

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    Group Project: Evaluation of an in-wheel motor drive for an electric car.

    Goal: Design a controller for an in-wheel synchronous motor in order to evaluate and determine its efficiency map. Use this information to propose powertrain solutions.

    Personal Contribution: Development of a motor drive using Triphase™ converters – modelling, sensor calibration.

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  • Design of a long range fully electric vehicle

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    Group Project: Design of a Long-range fully electric vehicle

    Goal: Propose powertrain solutions to convert an existing capsule to an electric vehicle capable of long distance travel

    Personal Contribution: Systems Engineering (The CAFCR framework), Market survey and analysis, Bill of Material analysis, estimation of requirements. I was also project leader for this module and took a lead role in project management, leadership and presentation.

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  • Model based Fault Diagnosers for the detection, isolation and identification of faults in automobile engine systems

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    • Modelling:
    A 4-stroke, 4-cylinder engine system with closed loop fuel injection and Exhaust Gas Recirculation (EGR) control was designed in the industry standard software tool AMESim™ and for the purposes of this work, simulates a real engine system. A mean value engine model (MVEM) that describes the dynamic averaged states of engine variables was developed in MATLAB™. This is based on a number of engine maps that are derived from simulation experiments on the original AMESim™ model.
    •…

    • Modelling:
    A 4-stroke, 4-cylinder engine system with closed loop fuel injection and Exhaust Gas Recirculation (EGR) control was designed in the industry standard software tool AMESim™ and for the purposes of this work, simulates a real engine system. A mean value engine model (MVEM) that describes the dynamic averaged states of engine variables was developed in MATLAB™. This is based on a number of engine maps that are derived from simulation experiments on the original AMESim™ model.
    • Estimation and Fault residual Generation:
    Input measurements and noisy asynchronous sensor measurements are obtained from the AMESim™ for a particular test profile. A post-processing algorithm was designed to suitably smoothen and fuse this data for use in Extended Kalman Filter (EKF) or Unscented Kalman Filters (UKF) based Estimators (State Observers). Several such Estimators work in parallel, each of which use an MVEM that has been suitably designed for a particular fault. The estimators use the fault model and the sensor measurements to estimate averaged states and generate appropriate fault residues.
    • Fault Diagnosis:
    The residues from parallel estimators are fed to the diagnoser that uses isolation logic based on the principles of structured residuals to detect, isolate and identify the fault. Thresholds for multi-level hypothesis testing is developed using statistical principles (risk functions) to reduce false alarm rates and missed detections. Dempster-Shafer’s theory of combination of evidence is used to combine the evidence from various hypothesis tests and to generate a final decision statement. In this work, an MVEM based fault Diagnoser was built to detect sensor faults and manifold leaks.

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Languages

  • English

    Native or bilingual proficiency

  • Dutch

    Elementary proficiency

  • German

    Elementary proficiency

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