Impact of Spark Assistance and Multiple Injections on Gasoline PPC Light Load

Along the last years, engine researchers are more and more focusing their efforts on the advanced low temperature combustion (LTC) concepts with the aim of achieving the stringent limits of the current emission legislations. In this regard, several studies based on highly premixed combustion concepts such as HCCI has been confirmed as a promising way to decrease drastically the most relevant CI diesel engine-out emissions, NOx and soot. However, the major HCCI drawbacks are the narrow load range, bounded by either misfiring (low load, low speed) or hardware limitations (higher load, higher speeds) and the combustion control (cycle-to-cylce control and combustion phasing). Although several techniques have been widely investigated in order to overcome these drawbacks, the high chemical reactivity of the diesel fuel remains as the main limitation for the combustion control. The attempts of the researchers to overcome these disadvantages are shifting to the use of fuels with different reactivity. In this sense, gasoline PPC has been able to reduce emissions and improve efficiency simultaneously, but some drawbacks regarding controllability and stability at low load operating conditions still need solution. In this field, previous researches have been demonstrate the multiple injection strategy as an appropriate technique to enhance the combustion stability. However, PPC combustion has been found limited to engine loads higher than 5 bar BMEP when using fuels with octane number greater than 90. In this regard, previous work from the authors showed the capability of the spark plug to provide combustion control in engine loads below this limit even using 98 ON gasoline. The main objective of the present work is to couple the control capability of the spark assistance together with an appropriate mixture distribution by using double injection strategies with the aim of evaluating performance and engine-out emissions at low load PPC range using a high octane number gasoline. For this purpose the optical and metal version of a compression ignition single-cylinder engine, to allow high compression ratio, has been used during the research. A common rail injection system enabling high injection pressures has been utilized to supply the 98 octane number gasoline. An analysis of the in-cylinder pressure signal derived parameters, hydroxyl radical (OH*) and natural luminosity images acquired from the transparent engine as well as a detailed analysis of the air/fuel mixing process by means of a 1-D in-house developed spray model (DICOM) has been conducted. Results from both analysis methods, suggest the spark assistance as a proper technique to improve the spatial and temporal control over the low load gasoline PPC combustion process. A noticeable increase in the cycle to cycle repeatability (5% versus 15.1% CoV IMEP at 2 bar load) as well as a reduction in the knocking level (20.5 versus 33.6 MW/m2 at 7 bar load) is observed. In addition, the combination of the spark assistance with the use of the double injection strategy provides a great improvement in terms of combustion efficiency (93% versus 88% for a single injection strategy) with a benefit around 18% in the IMEPBenajes Calvo, JV.; Tormos Martínez, BV.; García Martínez, A.; Monsalve Serrano, J. (2014). Impact of Spark Assistance and Multiple Injections on Gasoline PPC Light Load. SAE International Journal of Engines. 7(4):1875-1887. doi:10.4271/2014-01-2669S187518877

Assessment of low-viscosity oil performance and degradation in a heavy duty engine real-world fleet test

Low viscosity engine oils (LVO) are considered one of the most interesting solutions for improving fuel economy in internal combustion engines (ICE). There are different studies involving LVO and ICE, but currently limited data are available regarding real-world performance of LVO in a real service fleet. Included in a broadest study related with fuel consumption saving effects and performance of LVO in a real service fleet, the aim of this work is to present the results obtained in terms of comparative oil performance. So, on this test, a comparative analysis using 39 buses was performed, based on a deep and extensive oil analysis program to assess those aspects above mentioned. Two engine technologies (Diesel and CNG) were considered and four different lubricants, two of them LVO and other two used as a reference baseline. The test duration comprised two oil drain intervals of 30000 km each one, totalizing more than 2 million of kilometers accumulated. Results have shown that LVO presented an excellent performance along the oil drain interval (ODI), even improving some characteristics of the baseline oils with higher viscosity values. Results have shown that oil degradation is more dependent on engine technology, but in any case presented a penalization in terms of ODI reduction, a key indicator for end-users related with maintenance costs. In the case of CNG engines, higher oil degradation in terms of oil oxidation and nitration was observed.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Spanish Ministerio de Ciencia e Innovacion (Project no. TRA2012-30907).Macian Martinez, V.; Tormos Martínez, BV.; Miró Mezquita, G.; Pérez, T. (2016). Assessment of low-viscosity oil performance and degradation in a heavy duty engine real-world fleet test. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology. 230(6):729-743. doi:10.1177/1350650115619612S729743230

Low viscosity engine oils: Study of wear effects and oil key parameters in a heavy duty engine fleet test

Low viscosity engine oils (LVO) are considered key contributor for improving fuel economy in internal combustion engines (ICE). Attending that the use of LVO could imply a variation in tribological states found in ICE, this work's aim is to test LVO in real fleet, with emphasis on engine wear and oil key performance indicators. This test comprised 39 buses, two engine technologies and four different lubricants. For each sample, the elemental composition of the wear debris by ICP-AES and HTHS viscosity of the oil were measured among other properties. The results showed that, with a correct oil formulation, there is no significant difference when using LVO in terms of engine wear, HTHS viscosity variation and oil consumption. (C) 2015 Elsevier Ltd. All rights reserved.The authors would like to thank the Spanish Ministerio de Ciencia e Innovacion for its funding in this project (Project no. TRA2012-30907), and thank Repsol and EMT de Valencia for their collaboration. Additionally, the authors would like to thank Ruth Calatayud, Lorena Garzon, Leonardo Ramirez and Santiago Ballester for their help in this work.Macian Martinez, V.; Tormos Martínez, BV.; Ruiz Rosales, S.; Miró Mezquita, G. (2016). Low viscosity engine oils: Study of wear effects and oil key parameters in a heavy duty engine fleet test. Tribology International. 94:240-248. doi:10.1016/j.triboint.2015.08.028S2402489

A review of degradation process on compressed natural gas and diesel engines lubrican oils

[EN] In this study, a representative sample of urban buses, powered with CNG and diesel engine technologies and working on urban duty operation, have been studied in order to evaluate engine oil evolution of degradation. Main parameters evaluated have been related with oil degradation: oxidation, nitration, viscosity, Antioxidant additives depletion, antiwear, TAN, TBN and RUL Number. Results obtained have shown higher degradation rates for oils used on CNG engines than diesel engine. CNG engines studied showed a high thermal and mechanical stress, and lower oil sump volume. Experience with FT-IR technique on degradation study allowed to defi ne optimal spectral ranges to quantify the changes of oxidation, nitration and fuel dilution problem in MCIA[ES] En este estudio, una muestra representativa de autobuses de servicio urbano, con motorizaciones GNC y diesel, han sido estudiados con el fin de evaluar la evolución de la degradación de sus aceites. Los principales parámetros evaluados en relación con la degradación del aceite son: oxidación, nitración, viscosidad, agotamiento de los aditivos antioxidantes amínicos, antidesgaste, TAN, TBN y el número RUL. Los resultados obtenidos evidencian mayores tasas de degradación de los aceites usados en los motores GNC frente a los motores diesel. Los motores de GNC estudiados presentan una mayor exigencia a sus aceites al contar con mayores solicitaciones térmicas, mecánicas, y menor volumen del cárter de aceite. La experiencia adquirida con la aplicación de la técnica de FTIR para el estudio de la degradación, ha permitido definir rangos espectrales óptimos para cuantificar los cambios de oxidación, nitración y presencia de combustible en MCIA.Los autores quieren mostrar su agradecimiento al apoyo recibido desde el Ministerio de Ciencia e Innovación - Dirección General de Investigación: TRA2008-06508 (GLAUTO).Macian Martinez, V.; Tormos Martínez, BV.; Gomez Estrada, YA.; Bermúdez, V. (2013). Revisión del proceso de la degradación en los aceites lubricantes en motores de gas natural comprimido y diesel. DYNA: Ingeniería e Industria. 88(1):49-58. https://doi.org/10.6036/5077S495888

Monitoring and analysing oil condition to generate maintenance savings: a case study in a CNG engine powered urban transport fleet

The authors from Universitat Politecnica de Valencia wish to thank Spanish Grant TRA2008-06508 from Ministerio de Ciencia e Innovacion - Direccion General de Investigacion for supporting this work. Mr Gomez thanks the UPV for his grant 2011-S2-5003 in the frame of the PAID programme.Tormos Martínez, BV.; Olmeda González, PC.; Gomez Estrada, YA.; Galar, D. (2013). Monitoring and analysing oil condition to generate maintenance savings: a case study in a CNG engine powered urban transport fleet. Insight - Non-Destructive Testing & Condition Monitoring. 55(2):84-87. https://doi.org/10.1784/insi.2012.55.2.84S848755

Use of New Methodologies for Students Assessment in Large Groups in Engineering Education

[EN] In this paper, a student evaluation methodology which applies the concept of continuous assessment proposed by Bologna is presented for new degrees in higher education. An important part of the student's final grade is based on the performance of several individual works throughout the semester. The paper shows the correction system used which is based on using a spreadsheet with macros and a template in which the student provides the solution of each task. The employ of this correction system together with the available e-learning platform allows the teachers to perform automatic tasks evaluations compatible with courses with large number of students. The paper also raises the different solutions adopted to avoid plagiarism and to try that the final grade reflects, as closely as possible, the knowledge acquired by the students.Tormos Martínez, BV.; Climent, H.; Olmeda González, PC.; Arnau Martínez, FJ. (2014). Use of New Methodologies for Students Assessment in Large Groups in Engineering Education. Multidisciplinary Journal for Education, Social and Technological Sciences. 1(1):121-152. doi:10.4995/muse.2014.2198SWORD1211521

Findings from a fleet test on the performance of two engine oil formulations in automotive CNG engines

This work presents a comparative assessment of engine oil performance on field test using urban transport vehicles powered by compressed natural gas engines using two different mineral oil formulations approved by engine manufacturer. The first one is considered as a baseline reference, and the second one is a higher quality formulation in terms of base stock refining and additive content. Higher quality oil has shown a significant enhanced lubricant performance, leading to reach the oil drain interval defined by engine manufacturer on these engines without penalties in maintenance costs. In order to assess oil performance, an oil analysis programme has been established for oil samples collected from vehicles operated under real service conditions in an urban transport fleet. Monitored parameters include oxidation, nitration, aminic anti-oxidant additives depletion, anti-wear additives depletion, total acid number, total basic number and remaining useful life number (as an estimation of anti-oxidant additive depletion including aminic and zinc dialkyldithiophosphate). Results obtained in more than 90 samples from 15 different vehicles have shown higher degradation rates for low quality lubricant oil formulation. This deviation can be explained taking into account factors related with lower anti-oxidant additives content and lower thermal stability that can be mainly related with the base stock quality. This lower oil performance can be finally converted into higher vehicle maintenance cost and lower engine reliability.The authors wish thanks to the Spanish Grant TRA2008-06508 (GLAUTO) from the 'Ministerio de Ciencia e Innovacion - Direccion General de Investigacion' for supporting this work.Macian Martinez, V.; Tormos Martínez, BV.; Olmeda González, PC.; Gomez Estrada, YA. (2015). Findings from a fleet test on the performance of two engine oil formulations in automotive CNG engines. Lubrication Science. 27(1):15-28. https://doi.org/10.1002/ls.1248152827

Cálculo de la vida útil remanente mediante trayectorias móviles entre hiperplanos de máquinas de soporte vectorial

[EN] A novel remaining useful life (RUL) prediction method inspired by support vector machines (SVM) classifiers is proposed. The historical instances of a system with life-time condition data are used to create a classification by SVM hyper planes. For a test instance of the system whose RUL is to be estimated, degradation speed is evaluated by computing the minimal distance defined based on the degradation trajectories, i.e. the system approach to the hyperplane that segregates good and bad conditions data at different time horizons. Therefore, the final RUL of a specific component can be estimated and global RUL information can then be obtained by aggregating the multiple RUL estimates using a density estimation method. The degradation process of a system may be affected by many unknown factors that complicate the degradation behavior and also make it difficult to collect quality data. Due to lack of knowledge and incomplete measurements, certain important context information of the collected data might be missing. Therefore, historical data of the system with a large variety of degradation patterns is mixed together. With such data, learning a global model for RUL prediction becomes extremely hard. This has led to look for advanced RUL prediction techniques beyond the traditional prediction models. The proposed model develops an effective RUL prediction method that addresses multiple challenges in complex system prognostics. Similarities between degradation trajectories can be checked in order to enrich existing methodologies in prognostics applications. Existing condition monitoring data for bearings is used to validate the model.[ES] Se propone un nuevo método de predicción de vida útil remanente (RUL) inspirado en clasificadores de máquinas de soporte vectorial (SVM). Los datos históricos de condición de un sistema durante su tiempo de vida se utilizan para crear una clasificación mediante hiperplanos en SVM. Para estimar la RUL de un sistema, la velocidad de degradación se evalúa calculando la distancia mínima definida con base en las trayectorias de degradación; es decir, el acercamiento del sistema al hiperplano que segrega información de las condiciones buenas y malas en diferentes horizontes de tiempo. Se puede estimar la vida final de un componente específico, o la información de la RUL de una población ser calculada, mediante la agregación de múltiples estimaciones RUL usando un método de estimación de densidad. La degradación de un sistema se ve afectado por muchos factores desconocidos que, además de complicar los comportamientos de degradación, dificultan la recolección de datos con calidad. Debido a falta de conocimiento y medidas incompletas, normalmente se carece de información importante del contexto de los datos recogidos. Por ello se agrupan datos históricos del sistema con gran variedad de patrones de degradación, con los que la búsqueda de un modelo global de predicción RUL es extremadamente difícil. Esto lleva a buscar técnicas avanzadas de predicción más allá de los modelos tradicionales. El modelo propuesto desarrolla un método eficaz de predicción RUL que aborda múltiples retos en pronósticos de sistemas complejos. Las similitudes entre trayectorias de degradación pueden contrastarse para enriquecer las metodologías actuales de prognosis. Para verificar el modelo se emplean datos del monitorizado de condición en rodamientosGalar Pascual, D.; Berges Muro, L.; Lambán Castillo, MP.; Huertas Talón, JL.; Tormos Martínez, BV. (2013). Cálculo de la vida útil remanente mediante trayectorias móviles entre hiperplanos de máquinas de soporte vectorial. Interciencia: journal of science and technology of the Americas. 38(8):556-562. http://hdl.handle.net/10251/77486S55656238

Podejmowanie decyzji eksploatacyjnych w oparciu o fuzję różnego typu danych

[EN] Over the last decade, system integration is applied more as it allows organizations to streamline business processes. A recent development in the asset engineering management is to leverage the investment already made in process control systems. This allows the operations, maintenance, and process control teams to monitor and determine new alarm level based on the physical condition data of the critical machines. Condition-based maintenance (CBM) is a maintenance philosophy based on this massive data collection, wherein equipment repair or replacement decisions depend on the current and projected future health of the equipment. Since, past research has been dominated by condition monitoring techniques for specific applications; the maintenance community lacks a generic CBM implementation method based on data mining of such vast amount of collected data. The methodology would be relevant across different domains. It is necessary to integrate Condition Monitoring (CM) data with management data from CMMS (Computer Maintenance Management Systems) which contains information, such as: component failures, failure information related data, servicing or repairs, and inventory control and so on. These systems are the core of traditional scheduled maintenance practices and rely on bulk observations from historical data to make modifications to regulated maintenance actions. The most obvious obstacle in the integration of CMMS, process and CM data is the disparate nature of the data types involved, and there have benn several attempts to remedy this problem. Although, there have been many recent efforts to collect and maintain large repositories of these types of data, there have been relatively few studies to identify the ways these to datasets could be related. This paper attempts to fulfill that need by proposing a combined data mining-based methodology for CBM considering CM data and Historical Maintenance Management data. It shows a system integration of physical and management data that also supports business intelligence and data mining where data sets can be combined in non-traditional ways.[PL] W ostatniej dekadzie coraz częściej stosuje się integrację systemów, która pozwala przedsiębiorstwom zwiększać wydajność procesów biznesowych. Nowością w zarządzaniu infrastrukturą techniczną jest zwiększanie efektywności już poczynionych inwestycji w systemy kontroli procesów. Pozwala to zespołom do spraw operacyjnych, utrzymania ruchu oraz kontroli procesów monitorować i ustalać nowe poziomy alarmowe na podstawie danych o stanie fizycznym maszyn krytycznych. Utrzymanie urządzeń zależne od ich bieżącego stanu technicznego (condition-based maintenance, CBM) to filozofia utrzymania ruchu opierająca się na tym masowym poborze danych, wedle której decyzje dotyczące naprawy lub wymiany sprzętu zależą od jego obecnego oraz przewidywanego przyszłego stanu technicznego. Ponieważ dotychczasowe badania były zdominowane przez problem technik monitorowania stanu dla konkretnych aplikacji, nie opracowano ogólnej metody wdrażania CBM opartej na eksploracji (data mining ) owych olbrzymich ilości zebranych danych, która miałaby zastosowanie w różnych domenach. Konieczna jest integracja danych z monitorowania stanu (condition monitoring, CM) z danymi dotyczącymi zarządzania pochodzącymi ze skomputeryzowanych systemów zarządzania utrzymaniem ruchu (CMMS), które zawierają informacje na temat uszkodzeń elementów składowych, dane związane z uszkodzeniami, a także informacje dotyczące obsługi lub napraw czy sterowania zapasami. Systemy te stanowią podstawę tradycyjnych praktyk obsługi planowej, a zasadzają się na całościowych obserwacjach dokonywanych na podstawie danych eksploatacyjnych, które pozwalają modyfikować regulowane działania obsługowe. Najbardziej oczywistą przeszkodą w integracji danych CMMS, danych procesowych oraz danych z monitorowania stanu jest rozbieżność ich natury. Dotychczas podjęto jedynie kilka prób rozwiązania tego problemu. Chociaż ostatnio wiele wysiłku włożono w gromadzenie i utrzymanie dużych zasobów tego typu danych, istnieje stosunkowo niewiele badań na temat możliwych sposobów powiązania owych zestawów danych. W prezentowanej pracy poczyniono próbę wypełnienia tej luki proponując metodologię łączoną opartą na eksploracji danych dla celów CBM, która bierze pod uwagę dane z monitorowania stanu i eksploatacyjne dane z zarządzania ruchem. W pracy przedstawiono integrację systemową danych fizycznych i danych z zarządzania, która wspiera także analitykę biznesową (business intelligence) oraz eksplorację danych, gdzie zestawy danych można łączyć w sposób nietradycyjny.The author B. Tormos wish to thank “Programa de Apoyo a la Investigación y Desarrollo (PAID-00-11) de la Universitat Politècnica de València” for supporting his research.Galar, D.; Gustafson, A.; Tormos Martínez, BV.; Berges, L. (2012). Maintenance Decision Making based on different types of data fusion. Eksploatacja i Niezawodnosc - Maintenance and Reliability. 14(2):135-144. http://hdl.handle.net/10251/87630S13514414

Diagnóstico de motores de combustión interna álternativos mediante el análisis de las oscilaciones del bloque

This article presents a non-intrusive technique, designed for the Predictive Maintenance of alternative internal combustion engines (MCIA), based on the analysis of the oscillations of the block assuming the motor as a rigid body supported by elastic springs.These considerations allow The approximate determination of the instantaneous torque of the motor, using only and exclusively an accelerometer installed at a point of the block as far as possible from the crankshaft and recording the time signal of several thermodynamic cycles The signals thus obtained can inform about different types of failures, Especially those related to the different behavior between the cylinders.A simple physical model was used to estimate the performance of the engine under different operating conditions. The model has been validated through the realization of different experimental measurements both in engine test bench and in engines in service. Different tests have also been carried out to analyze the influence of the accelerometer position on the block.The final objective of the study is to determine alert and alarm limits of certain failures in the engine, such as injection or abnormal combustion in one or several cylinders. For this, it is necessary to analyze both the temporal and the frequency domain, a significant difference with the other techniques used for the diagnosis of machinery through vibrations.En este artículo se presenta una técnica no intrusiva, pensada para el Mantenimiento Predictivode motores de combustión interna alternativos (MelA), basada en el análisis de las oscilacionesdel bloque suponiendo el motor como un cuerpo rígido soportado por resortes elásticos. Estasconsideraciones permiten la determinación aproximada del par instantáneo del motor, utilizandoúnica y exclusivamente un acelerámetro instalado en un punto del bloque lo más alejado posibledel cigüeñal y registrando la señal temporal de varios ciclos termodinámicos. Las señal asíobtenida puede informar acerca de diferentes tipos de fallos, especialmente aquellos relativos aldiferente comportamiento entre los cilindros. Se utilizó un sencillo modelo físico para estimar el comportamiento del motor bajo diferentescondiciones defuncionamiento. El modelo ha sido validado a través de la realización de diferentesmedidas experimentales tanto en banco de ensayos de motor como en motores en servicio. Asimismose han realizado diferentes ensayos para analizar la influencia de la posición del acelerómetro en el bloque. El objetivo final del estudio es determinar límites de alerta y alarma de ciertos fallos en el motor,como puede ser la inyección o combustión anormal en uno o varios cilindros. Para ello se hacenecesario el análisis tanto en el dominio temporal como en el defrecuencia, diferencia importantecon el resto de técnicas utilizadas para el diagnóstico de maquinaria a través de vibraciones