On Board Diagnostics (OBD) Scan Tool to Diagnose Emission Control System

Climate change has become very important issue the world is facing today. To control impact of climate change and improve quality of life, one of the key factor targeted is vehicular emissions. To control emissions very stringent emission norms are introduced by various government agencies across the world. This called for increased use for electronics in the engines and vehicles. This complicates the matter at service and manufacturers. The engine computer (Electronic Control Unit) with international protocol like OBD is used to control electronic parameters in engines. This review paper describes emission compliance requirement with brief introduction of the OBD system along with scan tool to diagnose the system

Reliability challenges for automotive aftertreatment systems: a state-of-the-art perspective

YesThis paper provides a critical review and discussion of major challenges with automotive aftertreatment systems from the viewpoint of the reliability of complex systems. The aim of this review is to systematically explore research efforts towards the three key issues affecting the reliability of aftertreatment systems: physical problems, control problems and fault diagnostics issues. The review covers important developments in technologies for control of the system, various methods proposed to tackle NOx sensor cross-sensitivity as well as fault detection and diagnostics methods, utilized on SCR, LNT and DPF systems. This paper discusses future challenges and research direction towards assured dependability of complex cyber-physical systems.InPowerCare Project - JLR (Jaguar Land Rover

A predictive dynamic model of a smart cogeneration plant fuelled with fast pyrolysis bio-oil

Small scale biomass-based cogeneration has the potential to contribute significantly to a clean, flexible, secure, and cost-efficient energy system. It provides flexibility to future energy systems by balancing variable intermittent renewable energy sources. To exploit its flexibility, a smart control unit is needed. To enable smart control of a cogeneration unit, and to determine its optimal working points, a dynamic system model is required. The purpose of this study is to develop, parameterize and tune a dynamic model of a cogeneration plant fuelled with fast pyrolysis bio-oil. The system is a hybrid diesel generator/flue gas boiler plant for electricity generation and water/space heating. The plant has two unique features: (i) pyrolysis bio-oil is a new fuel for both engine and boiler, and as such it influences their operation and emissions, (ii) power and heat generation are partially decoupled hence non-linearly correlated. The paper presents the integration of the components’ dynamic models into a system model. The model is parameterized and partially validated using measurements from a turbocharged four-cylinder diesel engine and a swirl burner both running on FPBO. Preliminary controls are designed and evaluated. Results show applicability and usefulness of the model for cogeneration system analysis and control design evaluation

Control-oriented modelling and diagnostics of diesel after-treatment catalysts

[ES] Esta tesis doctoral abarca el desarrollo de algoritmos orientados a mejorar el sistema de control de emisiones en motores Diesel. Para este propósito, la inclusión en el vehículo de sensores embarcados como los de temperatura, los de NOx o el de NH3 permite realizar diagnóstico a bordo de los sistemas de post-tratamiento foco de este trabajo, los cuales son el DOC y el SCR. Así pues, el objetivo es el de satisfacer las normativas de diagnóstico a bordo para mantener las emisiones por debajo del umbral permitido por la normativa a lo largo del tiempo. Los tests experimentales, incluyendo las medidas con analizador de gases, permiten tener una visión más amplia de las especies en la línea de escape. Complementariamente, se utilizan unidades nuevas y envejecidas para tener el efecto experimental del envejecimiento en los catalizadores. De esta manera, se analiza el efecto de la temperatura, el gasto de escape, las concentraciones de las especies y el envejecimiento en el DOC y en el SCR, así como la evaluación de algunas de las medidas relevantes realizadas por los sensores. Las temperaturas tienen una influencia destacada en el funcionamiento de los catalizadores, por lo que se requiere la evaluación de las medidas de los sensores de temperatura, junto con el desarrollo de modelos de transmisión de calor, para alimentar las funciones a continuación desarrolladas. En este sentido, la medida lenta del sensor aguas arriba del DOC se mejora en condiciones transitorias mediante una técnica de fusión de la información basada en un filtro de Kalman. Luego, se presenta un modelo de transmisión de calor 1D y un modelo agrupado 0D, en los cuales se evalúan las entradas aguas arriba según el uso del modelo. Por otra parte, se presenta una técnica para estimar el incremento de temperatura debido a la oxidación de los pulsos de post-inyección en el DOC. Se proponen modelos para ambos DOC y SCR para estimar el efecto del envejecimiento en las emisiones, en los cuales el factor de envejecimiento es modelado como un parámetro sintonizable que permite variar desde estados nuevos a envejecidos. Por una parte, un modelo agrupado 0D es desarrollado para el DOC con el propósito de estimar el desliz de HC y CO, el cual es validado en un WLTC para después ser usado en simulación. Por otra parte, un modelo 1D y un modelo 0D se desarrollan para el SCR, los cuales se usan a continuación para alimentar la estrategia de diagnóstico y para simulación. Finalmente, las estrategias de diagnóstico se presentan para fallo total o retirada de DOC, así como para la estimación de la eficiencia en DOC y SCR. Por una parte, la primera estrategia se divide en pasiva y activa, en la que se usan post-inyecciones en la activa para excitar el sistema y confirmar el fallo total si es el caso. A continuación, la eficiencia del DOC se estima a través de una técnica indirecta en la que la temperatura de activación se detecta y se relaciona con el incremento de emisiones a través del modelo. Por otra parte, se desarrolla un observador para estimar el estado de envejecimiento del SCR, el cual está basado en un filtro de Kalman extendido. Sin embargo, para evitar asociar baja eficiencia del catalizador debido a pobre calidad de la urea inyectada, a envejecimiento del SCR, un indicador de la calidad de la urea se ejecuta en paralelo.[CA] Esta tesi doctoral abasta el desenvolupament d'algoritmes orientats a millor el sistema de control d'emissions en motors Diesel. Per a este propòsit, la inclusió en el vehicle de sensor embarcats com els de temperatura, els de NOx o el d'NH3 permet realitzar el diagnòstic a bord dels sistemes de post-tractament focus d'este treball, els quals són el DOC i el SCR. Així doncs, l'objectiu és el de satisfer les normatives de diagnòstic a bord per a mantindre les emissions per baix de l'umbral permés per la normativa al llarg del temps. Els tests experimentals, incloent les mesures amb analitzador de gasos, permeten obtindre una visió més àmplia de les espècies en la línia d'escapament. Complementàriament, s'utilitzen unitats noves i envellides per tal de tindre l'efecte experimental de l'envelliment en els catalitzadors. D'aquesta manera, s'analitza l'efecte de la temperatura, la despesa d'escapament, les concentracions de les espècies i l'envelliment en el DOC i en el SCR, així com l'avaluació d'algunes mesures rellevants realitzades pels sensors. Les temperatures tenen una influència destacada en el funcionament dels catalitzadors, pel que es requerix l'avaluació de les mesures dels sensors de temperatura, junt amb el desenvolupament de models de transmissió de calor, per a alimentar les funcions a continuació desenvolupades. En este sentit, la mesura lenta del sensor a l'entrada del DOC es millora en condicions transitòries mitjançant una tècnica de fusió de la informació basada en un filtre de Kalman. Després, es presenta un model de transmissió de calor 1D i un model agrupat 0D, en els quals s'avaluen les entrades a l'entrada segons l'ús del model. Per altra banda, es presenta una tècnica per a estimar l'increment de temperatura degut a l'oxidació dels polsos de post-injecció en el DOC. Es proposen models per a DOC i SCR per a estimar l'efecte de l'envelliment en les emissions, en els quals es modela el factor d'envelliment com un paràmetre sintonitzable, que permet variar des d'estats nous a envellits. Per altra banda, un model agrupat 0D _es desenvolupat per al DOC amb el propòsit d'estimar la relliscada de HC i CO, el qual és validat en un WLTC per a després ser usat en simulació. Per altra banda, un model 1D i un model 0D es desenvolupen per al SCR, els quals s'usen a continuació per a alimentar l'estratègia de diagnòstic i per a simulació. Finalment, les estratègies de diagnòstic es presenten per a la fallada total o retirada del DOC, així com per a l'estimació de l'eficiència en DOC i SCR. Per altra banda, la primera estratègia es divideix en passiva i activa, en la que s'utilitzen post-injeccions en la activa per a excitar el sistema i confirmar la fallada total si es dona el cas. A continuació, l'eficiència del DOC s'estima a través d'una tècnica indirecta en la que la temperatura d'activació es detecta i es relaciona amb l'increment d'emissions a través del model. Per altra banda, es desenvolupa un observador per a estimar l'estat d'envelliment del SCR, el qual està basat en un filtre de Kalman extés. No obstant això, per a evitar associar baixa eficiència degut a pobre qualitat de l'urea injectada a l'envelliment del SCR, un indicador de la qualitat de l'urea s'executa en paral·lel.[EN] This dissertation covers the development of algorithms oriented to improve the emission control system of Diesel engines. For this purpose, the inclusion of on-board sensors like temperature, NOx and NH3 sensors allows performing on-board diagnostics to the after-treatment systems focus of this work, which are the DOC and the SCR system. Then, the target is to meet on-board diagnostics regulations in order to keep emissions below a regulation threshold over time. Experimental tests, including gas analyzer measurements, allow having a wider view of the species in the exhaust line. Complementary, new and aged units are used in order to have the experimental effect of ageing on the catalysts. Then, the effect of temperature, exhaust mass flow, species concentrations and ageing is analyzed for DOC and SCR, in combination with the assessment of some relevant sensors measurements. As a result, the characteristics, opportunities and limitations extracted from experimental data are used as the basis for the development of models and diagnostics techniques. The assessment of temperature sensors measurements, along with the development of heat transfer models is required to feed temperature dependent functions. In this sense, the slow measurement of the DOC upstream temperature sensor is improved in transient conditions by means of a data fusion technique, based on a fast model and a Kalman filter. Then, a 1D and a 0D lumped heat transfer models are presented, in which the upstream inputs are assessed in relation to its use. On the other hand, a technique to estimate the temperature increase due to post-injection pulses oxidation is also presented. Both DOC and SCR models are proposed in order to estimate the effect of ageing on emissions, in which an ageing factor is modelled as a tunable parameter that allows varying from new to aged states. On the one hand, a 0D lumped model is developed for DOC in order to estimate the HC and CO species slip, which is validated in a WLTC and is then used for simulation. On the other hand, a 1D and a 0D models are developed for SCR, which are then used to feed the diagnostics strategy and for simulation. Finally, diagnostics strategies are presented for total failure or removal of DOC, as well as for efficiency estimation of DOC and SCR. On the one hand, the former strategy is separated into passive and active diagnostics, in which post-injections are used in active diagnostics in order to excite the system and confirm a total failure, in case. Then, the DOC efficiency estimation is done by means of an indirect technique in which the light-off temperature is detected and an emissions increase is related by means of the DOC ageing model. On the other hand, an observer to estimate the SCR ageing state is developed, which is based on an extended Kalman filter. However, in order to avoid associating low SCR efficiency to ageing, an indicator of the injected urea quality is developed to run in parallel.Mora Pérez, J. (2018). Control-oriented modelling and diagnostics of diesel after-treatment catalysts [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115937TESI

Training Based Testing Of Temperature Sensors In Diesel Engine Aftertreatment System

The goal of this thesis is to research the possibility for creating an automated test for verifying the correct installation of temperature sensors in a diesel exhaust aftertreatment system. Both model and training based solutions are discussed. The implementation is done by training multiple machine learning models and comparing their results. Data was specifically collected for this research. Data collection consisted of taking measurements from a test engine using different sensor combinations. In total there were four different sensor combinations and for each combination 25 recordings were taken. The recordings had variating starting temperatures. The data was then labeled accordingly for supervised learning. Results show that classification of sensor installations can be achieved with high accuracy. All the used models provide promising results while logistic regression model seems perform the best. More important and limiting issue is the data gathering process for training and testing the models

Real-time implementation of a sensor validation scheme for a heavy-duty diesel engine

With ultra-low exhaust emissions standards, heavy-duty diesel engines (HDDEs) are dependent upon a myriad of sensors to optimize power output and exhaust emissions. Apart from acquiring and processing sensor signals, engine control modules should also have capabilities to report and compensate for sensors that have failed. The global objective of this research was to develop strategies to enable HDDEs to maintain nominal in-use performance during periods of sensor failures. Specifically, the work explored the creation of a sensor validation scheme to detect, isolate, and accommodate sensor failures in HDDEs. The scheme not only offers onboard diagnostic (OBD) capabilities, but also control of engine performance in the event of sensor failures. The scheme, known as Sensor Failure Detection Isolation and Accommodation (SFDIA), depends on mathematical models for its functionality. Neural approximators served as the modeling tool featuring online adaptive capabilities. The significance of the SFDIA is that it can enhance an engine management system (EMS) capability to control performance under any operating conditions when sensors fail. The SFDIA scheme updates models during the lifetime of an engine under real world, in-use conditions. The central hypothesis for the work was that the SFDIA scheme would allow continuous normal operation of HDDEs under conditions of sensor failures. The SFDIA was tested using the boost pressure, coolant temperature, and fuel pressure sensors to evaluate its performance. The test engine was a 2004 MackRTM MP7-355E (11 L, 355 hp). Experimental work was conducted at the Engine and Emissions Research Laboratory (EERL) at West Virginia University (WVU). Failure modes modeled were abrupt, long-term drift and intermittent failures. During the accommodation phase, the SFDIA restored engine power up to 0.64% to nominal. In addition, oxides of nitrogen (NOx) emissions were maintained at up to 1.41% to nominal

A novel framework for enhancing marine dual fuel engines environmental and safety performance via digital twins

The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping.The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping

Risk analysis of the LHC underground area: fire risk due to faulty electrical equipment

The European Organisation for Nuclear Research (CERN) in Geneva, Switzerland, is currently building the latest generation of particle accelerators, the LHC (Large Hadron Collider). The machine is housed in a circular tunnel of 27 km of circumference and is situated approximately 100 metres beneath the surface astride the Franco-Swiss border. Electrically induced fires in the LHC are a major concern, since an incident could present a threat to CERN personnel as well as the public. Moreover, the loss of equipment would result in significant costs and downtime. However, the amount of electrical equipment in the underground area required for operation, supervision and control of the machine is essential. Thus the present thesis is assessing the risk of fire due to faulty electrical equipment in both a qualitative as well as quantitative way. The recommendations following the qualitative analysis suggest the introduction of fire protection zones for the areas with the highest risk of fire due to a combination of possible ignition sources and combustible material in the vicinity. In order to be able to conduct regular follow-up examinations to obtain more precise results for the quantitative analysis in the future, the creation of a material data inventory and the collection of failure probability data throughout the lifetime of the LHC are recommended

Articles publicats per investigadors de l'ETSEIB. Producció científica a Futur 2015

Postprint (author's final draft