Design and Selection of Additional Residuals to Enhance Fault Isolation of a Turbocharged Spark Ignited Engine System

This paper presents a method to enhance fault isolation without adding physical sensors on a turbocharged spark ignited petrol engine system by designing additional residuals from an initial observer-based residuals setup. The best candidates from all potential additional residuals are selected using the concept of sequential residual generation to ensure best fault isolation performance for the least number of additional residuals required. A simulation testbed is used to generate realistic engine data for the design of the additional residuals and the fault isolation performance is verified using structural analysis method.Comment: 6 pages, 10 figures, To appear in 7th International Conference on Control, Decision and Information Technologies (CoDIT'20

Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan

This paper presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this paper, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.Comment: 35 pages, 7 figures, To appear in Peer

A Realistic Simulation Testbed of A Turbocharged Spark-Ignited Engine System: A Platform for the Evaluation of Fault Diagnosis Algorithms and Strategies

Research on fault diagnosis on highly nonlinear dynamic systems such as the engine of a vehicle have garnered huge interest in recent years, especially with the automotive industry heading towards self-driving technologies. This article presents a novel opensource simulation testbed of a turbocharged spark ignited (TCSI) petrol engine system for testing and evaluation of residuals generation and fault diagnosis methods. Designed and developed using Matlab/Simulink, the user interacts with the testbed using a GUI interface, where the engine can be realistically simulated using industrial-standard driving cycles such as the Worldwide harmonized Light vehicles Test Procedures (WLTP), the New European Driving Cycle (NEDC), the Extra-Urban Driving Cycle (EUDC), and EPA Federal Test Procedure (FTP-75). The engine is modeled using the mean value engine model (MVEM) and is controlled using a proportional-integral (PI)-based boost controller. The GUI interface also allows the user to induce one of the 11 faults of interest, so that their effects on the performance of the engine are better understood. This minimizes the risk of causing permanent damages to the engine and shortening its lifespan, should the tests be conducted onto the actual physical system. This simulation testbed will serve 16 as an excellent platform where researchers can generate critical data to develop and compare current and future research methods for fault diagnosis of automotive engine systems.Comment: 64 pages, 23 figures, To appear in IEEE Control System

Development of a mathematical model to predict the health impact and duration of SARS-CoV-2 outbreaks on board cargo vessels

The Coronavirus Disease (COVID-19) pandemic has brought significant impact onto the maritime activities worldwide, including disruption to global trade and supply chains. The ability to predict the evolution and duration of a COVID-19 outbreak on cargo vessels would inform a more nuanced response to the event and provide a more precise return-to-trade date. This paper presents the SEIQ(H)R (Susceptibility–Exposed–Infected–Quarantine–(Hospitalisation)–Removed/Recovered) model, which is the first deterministic mathematical model developed and fit-tested to describe the transmission dynamics of COVID-19 on board cargo vessels of up to 60 crew members. Due to specific living and working circumstances on board cargo vessels, instead of utilising the reproduction number, we consider the highest fraction of crew members who share the same nationality to quantify the transmissibility of the disease. The performance of the model is verified using case studies based on data collected during COVID-19 outbreaks on three cargo vessels in Western Australia during 2020. The simulations show that the model can forecast the time taken for the transmission dynamics on each vessel to reach their equilibriums, providing informed predictions on the evolution of the outbreak, including hospitalisation rates and duration. The model demonstrates that (a) all crew members are susceptible to infection; (b) their roles on board are a determining factor in the evolution of the outbreak; and (c) an unmitigated outbreak could affect the entire crew and continue on for many weeks. The ability to model the evolution of an outbreak, in both duration and severity, is essential to predict outcomes and to plan for the best response strategy. At the same time, it offers a higher degree of certainty regarding the return to trade, which is of significant importance to multiple stakeholders