Browsing by Author "Devaraj, Lokesh"

Now showing 1 - 9 of 9
  • Thumbnail Image
    ItemOpen Access
    Application of probabilistic models for multitone electromagnetic immunity analysis
    (IEEE, 2022-10-12) Devaraj, Lokesh; Khan, Qazi Mashaal; Ruddle, Alastair R.; Duffy, A. P.; Perdriau, Richard; Koohestani, Mohsen
    The operational environment of modern electronic systems may include multiple frequency electromagnetic dis- turbances. However, immunity measurements usually employ single frequency continuous waveforms (i.e. single-tones). The performance of two oscillator circuits with different topologies (one simulated and one measured) were used as case studies to in- vestigate immunity to simultaneous single-tone disturbances (i.e. multitones) using probabilistic Bayesian network models. For the multitone analysis, the noisy-OR model was first used to identify the type of causal interactions between simultaneously occurring single-tones. Probabilistic theories derived from the recursive noisy-OR model, which inherits the independence assumptions of the noisy-OR and any known causal dependence between simultaneously occurring single-tones, were then used to predict the probability of higher order multitone failures. For the two case studies, the probability of three-tone failures was estimated using the single-tone and two-tone failure probability values. An improved adaptive recursive noisy-OR model was also proposed to overcome the practical difficulties of obtaining multitone failure probabilities, from either simulations or measurements.
  • Thumbnail Image
    ItemOpen Access
    Comparing Simulated Impact of Single Frequency and Multitone EMI for an Integrated Circuit
    (IEEE, 2022-04-21) Devaraj, Lokesh; Khan, Qazi Mashaal; Ruddle, Alastair; Duffy, Alistair
    Electromagnetic immunity performance characteristics for integrated circuits are currently verified using tests involving single-frequency continuous wave disturbances. In real operational environments, however, systems may be exposed to simultaneous interference sources at multiple frequencies. Simulation results obtained for the electromagnetic susceptibility of a simple voltage-controlled oscillator to randomly generated multitone interference are compared with corresponding data obtained for single frequencies. The results obtained are used to assess the validity of the current approach of testing circuit designs for immunity using single frequency noise source. Notable differences in the output response of the circuit to single and multitone interference, which could possibly lead to system malfunctions, are illustrated.
  • Thumbnail Image
    ItemOpen Access
    Electromagnetic Risk Analysis for EMI Impact on Functional Safety with Probabilistic Graphical Models and Fuzzy Logic
    (IEEE, 2020) Devaraj, Lokesh; Ruddle, Alastair; Dufffy, Alistair
    For the functional safety and security of complex systems such as road vehicles, sufficient immunity of the safety-related electronic, electrical and programmable electronic systems to the anticipated electromagnetic environment is required. Current rule-based practices follow established standards for testing the immunity and emission performance at vehicle and sub-system levels. Nonetheless, with increasingly rapid technological changes, confidence may not be sufficient even if the immunity test levels or the number of tests is increased. A risk-based approach, on the other hand, aims to identify the safety hazards (due to electromagnetic disturbances) and mitigate the associated risks to achieve the required confidence level. However, the traditional tools used for risk analysis (such as fault tree analysis, event tree analysis and failure mode and effect analysis) may not be sufficient as the complexity level increases. In this paper, a graphical approach proposed to enable system visualization as well as supporting a comprehensive risk analysis. The possible implementation of a system-level analysis is illustrated with several methods (e.g. Bayesian networks, Markov random fields and fuzzy set theory), which could be used for estimation of system level.
  • Thumbnail Image
    ItemOpen Access
    Electromagnetic Risk Management for Dependability of Road Vehicles using Discrete Bayesian Networks
    (De Montfort University, 2023) Devaraj, Lokesh
    The analysis of functional safety, cybersecurity and other risks has become an integral part of the development of modern road vehicles, which are increasingly reliant on the correct functioning of lectrical/electronic/programmable electronic (E/E/PE) systems. Electromagnetic interference (EMI) originating from on-board and off-board radio frequency (RF) sources are well-known common cause of failures or malfunctions in E/E/PE systems. Although vehicle electromagnetic compatibility (EMC) requirements take some account of safety issues, they are mainly concerned with interoperability and their separate and independent development means that they are not directly connected with the more recently developed interests in other dependability aspects e.g., cybersecurity. From the system assessor’s perspective, functional safety issues caused by EMI have mostly been believed to be handled by legislative EMC measures. However, this position is highly questionable for systems that contain new technologies that are not considered in existing EMC standards. A unified approach that enables EMC risk management for the wider aspects of vehicle resilience as well as for functional safety and cybersecurity would increase the efficiency of the additional analyses by promoting the sharing and reuse of information. Based on the identified challenges for adopting a risk-based EMC approach, the application of probabilistic graphical models called Bayesian network (BN) is proposed in this thesis for two main purposes. First, to graphically model the epistemic uncertainties considered for electromagnetic (EM) immunity risk assessment, second, to overcome the limitations of assessing EMI risks due to multiple disturbances that can be simultaneously present (multitone) in the system EM environment. Two new multi-causal effect prediction models are proposed in this thesis to predict the failure probability of E/E/PE systems due to multitone EMI. The proposed models are verified with experiments to have an enhanced prediction accuracy when compared to the existing models in literature.
  • Thumbnail Image
    ItemOpen Access
    EMI Risk Estimation for System-Level Functions Using Probabilistic Graphical Models
    (IEEE, 2021-10-19) Devaraj, Lokesh; Ruddle, Alastair; Duffy, Alistair
    In general, the functions provided by complex systems often involve multiple sub-systems and components that are functionally dependent on each other. The dependency could be to receive power, control signals, input data, memory storage, feedback etc. With the increasing use of electronic systems to perform critical functions, the potential for malfunctions due to electromagnetic interference need to be identified and mitigated. Hence, a risk analysis, estimating the likelihood and severity of electromagnetic interference effects, is desirable from the very early stages of system development. In this paper, the use of probabilistic graphical models for estimating the likelihood of electromagnetic disturbances causing system malfunctions with various degrees of severity is demonstrated using a very simple case study. Statistical data are synthesised to illustrate the construction of conditional probability distribution tables for a Bayesian Network system model. Factorization and inference techniques are then applied to demonstrate the formulation and answer of queries that could be of value during system risk assessment.
  • No Thumbnail Available
    ItemMetadata only
    Improvements proposed to noisy-OR derivatives for multi-causal analysis: A case study of simultaneous electromagnetic disturbances
    (Elsevier, 2023-11-09) Devaraj, Lokesh; Khan, Qazi Mashaal; Ruddle, Alastair R.; Duffy, A. P.; Perdriau, Richard; Koohestani, Mohsen
    In multi-causal analysis, the independence of causal influence (ICI) assumed by the noisy-OR (NOR) model can be used to predict the probability of the effect when several causes are present simultaneously, and to identify (when it fails) inter-causal dependence (ICD) between them. The latter is possible only if the probability of observing the multi-causal effect is available for comparison with a corresponding NOR estimate. Using electromagnetic interference in an integrated circuit as a case study, the data corresponding to the probabilities of observing failures (effect) due to the injection of individual (single cause) and simultaneous electromagnetic disturbances having different frequencies (multiple causes) were collected. This data is initially used to evaluate the NOR model and its existing derivatives, which have been proposed to reduce the error in predictions for higher-order multi-causal interactions that make use of the available information on lower-order interactions. Then, to address the identified limitations of the NOR and its existing derivatives, a new deterministic model called Super-NOR is proposed, which is based on correction factors estimated from the available ICD information.
  • Thumbnail Image
    ItemOpen Access
    Knowledge-Based Approach for System Level Electromagnetic Safety Analysis
    (2021-09-19) Devaraj, Lokesh; Ruddle, Alastair; Khan, Qazi Mashaal; Duffy, Alistair
    Road vehicles and similarly complex systems are constructed by integrating many subsystems and components that are sourced from a large number of suppliers. This process may lead to the emergence of possible system-level safety issues, some of which could be caused by external or internal electromagnetic interference. Assurance of safety by demonstrating compliance with standard tests is becoming increasingly challenging as system complexity rises. This is due to the costs and practical limitations of both component and system-level electromagnetic compatibility testing. Hence, there is a need for additional methods to help estimate the likelihood of electromagnetic interference risks associated with such systems. Probabilistic graphical models, such as Bayesian and Markov networks, are able to provide a better visualization of various features and their relationships in a single graphical structure. Moreover, using template models, a general-purpose representation for various integrated components of a system can be developed for collective inference. Using such methods, this paper proposes a knowledge-based approach to assist risk management in system-level electromagnetic engineering. The purpose of using a knowledge-based approach is to be able to undertake safety risk analyses during the early stages of design, when many factors (e.g. internal, and external electromagnetic interference levels, physical location of the component) remain uncertain.
  • Thumbnail Image
    ItemOpen Access
    Risk Assessment Approach for EM Resilience in Complex Systems Using Bayesian Networks
    (IEEE, 2021-08) Devaraj, Lokesh; Ruddle, Alastair; Duffy, Alistair; Martin, Anthony
    Current trends in the automotive industry are reshaping the architectures and electromagnetic characteristics of road vehicles. Increasing electrification and connectivity are enabling considerable packaging flexibility and leading to radically different electromagnetic environments. At the same time, increasing automation of driving functions will require unprecedented levels of system dependability. However, existing EMC engineering processes were developed in a very different world of low system complexity and incremental technological development. In order to adapt to rising system complexity and the increasingly rapid pace of technological change, it is considered that a more agile risk-based approach is better suited to ensure the electromagnetic resilience of future vehicles and other complex systems. This paper outlines a Bayesian network approach that allows the combination of both technical and nontechnical aspects in assessing the likelihood of issues that could lead to system-level risks. This approach could be used from the earliest stages of product development, where the detailed information required to undertake detailed risk assessment is generally unavailable.
  • Thumbnail Image
    ItemOpen Access
    System Level Risk Analysis for Immunity in Automotive Functional Safety Analyses
    (IEEE, 2020-09-23) Devaraj, Lokesh; Ruddle, Alastair; Duffy, Alistair; Martin, A.J.M.
    At present, automotive functional safety and EMC engineering are largely carried out independently. Current EMC regulations aim to avoid unwanted disturbances by setting appropriate immunity threat levels and emission limits. However, with the rapidly evolving technology and complexity of automotive systems, the limits identified in standards may no longer be appropriate. Hence the identification and assessment of EMC-related risks are becoming increasingly necessary. This paper outlines the tools used to support risk analysis for functional safety and presents initial proposals for a graphical method to better align the analysis of EMC risks and functional safety.