Create Cost Effective Post Processing Techniques for Multiple Measured and Simulated Components of CVT Transmissions

The automotive industry requires continuous innovation in order to fight the high competitiveness in this sector. More than ever, fuel economy, low emissions and comfort are the main goals when designing a vehicle. Continuously Variable Transmissions (CVT) are a type of transmissions that meet with those features and it can be the future of automatic transmissions. The presented dissertation was developed during an internship in a company, specialist in the development and production of CVT transmissions, designated by Punch Powertrain NV, located in Sint-Truiden, Belgium. The work was incorporated in the Research and Development (R&D) department, in the team of simulation, where it was possible to enhance the academic experience. This work is based on a need to post-process the results of several measured and simulated scenarios. Firstly, it was proposed to analyse the interference between the components of a hydraulic block. After the block is simulated individually, the inside walls can deform and it is important to analyse if there is interference with the movable components. Secondly, there are corrections done on gears. These corrections are evaluated through gear measurements, which need to be processed to determine if the modifications are within the nominal parameters. The last task was to analyse exported data from road load tests. In each transmission, five accelerometers are installed that record the loads subjected in the three coordinates. These files are read and, then, processed using an algorithm of a counting method, that can predict the cycles of each accelerometer for the different loads. All results are validated by the team leader and the specialists of each field. In the end, the internship allowed to increase the knowledge obtained from the Master’s.A indústria automóvel exige uma inovação contínua, de forma a combater a elevada competitividade neste setor. Mais do que nunca, economia de combustível, baixas emissões e conforto são as principais características na hora de desenhar um veículo. Transmissões Continuamente Variáveis (CVT) são um tipo de transmissão que cumpre esses objetivos e pode ser o futuro das transmissões automáticas. A presente dissertação foi desenvolvida durante um estágio numa empresa especialista no desenvolvimento e produção de transmissões CVT, com o nome de Punch Powertrain NV e localizada em Sint-Truiden, Bélgica. O trabalho foi inserido no departamento de Inovação e Desenvolvimento (I&D), na equipa de simulação, onde foi possível enriquecer a experiência académica. Este trabalho teve por base a necessidade de pós-processar os resultados de diversos cenários medidos e simulados. Em primeiro lugar, foi proposto analisar a interferência entre os componentes de um bloco hidráulico. Depois do bloco ser simulado individualmente, as paredes interiores podem deformar e é importante analisar se existe interferência com as componentes móveis. Em segundo lugar, existem correções feitas em rodas dentadas, para que possam trabalhar corretamente. Então, estas correções são analisadas através de medições, que precisam de ser processadas para determinar se as modificações estão dentro dos parâmetros nominais. A última tarefa foi analisar informação exportada dos testes de carga na estrada. Em cada transmissão, são instalados cinco acelerómetros que registam as cargas submetidas nas três coordenadas. Esses ficheiros são lidos e, depois, processados usando um algoritmo de contagem, que consegue prever os ciclos de cada acelerómetro para as diferentes cargas. Todos os resultados são validados pelo líder de equipa e pelos especialistas de cada área. No final, o estágio permitiu aumentar o conhecimento obtido durante o mestrado

Optimal Control for Automotive Powertrain Applications

Optimal Control (OC) is essentially a mathematical extremal problem. The procedure consists on the definition of a criterion to minimize (or maximize), some constraints that must be fulfilled and boundary conditions or disturbances affecting to the system behavior. The OC theory supplies methods to derive a control trajectory that minimizes (or maximizes) that criterion. This dissertation addresses the application of OC to automotive control problems at the powertrain level, with emphasis on the internal combustion engine. The necessary tools are an optimization method and a mathematical representation of the powertrain. Thus, the OC theory is reviewed with a quantitative analysis of the advantages and drawbacks of the three optimization methods available in literature: dynamic programming, Pontryagin minimum principle and direct methods. Implementation algorithms for these three methods are developed and described in detail. In addition to that, an experimentally validated dynamic powertrain model is developed, comprising longitudinal vehicle dynamics, electrical motor and battery models, and a mean value engine model. OC can be utilized for three different purposes: 1. Applied control, when all boundaries can be accurately defined. The engine control is addressed with this approach assuming that a the driving cycle is known in advance, translating into a large mathematical problem. Two specific cases are studied: the management of a dual-loop EGR system, and the full control of engine actuators, namely fueling rate, SOI, EGR and VGT settings. 2. Derivation of near-optimal control rules, to be used if some disturbances are unknown. In this context, cycle-specific engine calibrations calculation, and a stochastic feedback control for power-split management in hybrid vehicles are analyzed. 3. Use of OC trajectories as a benchmark or base line to improve the system design and efficiency with an objective criterion. OC is used to optimize the heat release law of a diesel engine and to size a hybrid powertrain with a further cost analysis. OC strategies have been applied experimentally in the works related to the internal combustion engine, showing significant improvements but non-negligible difficulties, which are analyzed and discussed. The methods developed in this dissertation are general and can be extended to other criteria if appropriate models are available.El Control Óptimo (CO) es esencialmente un problema matemático de búsqueda de extremos, consistente en la definición de un criterio a minimizar (o maximizar), restricciones que deben satisfacerse y condiciones de contorno que afectan al sistema. La teoría de CO ofrece métodos para derivar una trayectoria de control que minimiza (o maximiza) ese criterio. Esta Tesis trata la aplicación del CO en automoción, y especialmente en el motor de combustión interna. Las herramientas necesarias son un método de optimización y una representación matemática de la planta motriz. Para ello, se realiza un análisis cuantitativo de las ventajas e inconvenientes de los tres métodos de optimización existentes en la literatura: programación dinámica, principio mínimo de Pontryagin y métodos directos. Se desarrollan y describen los algoritmos para implementar estos métodos así como un modelo de planta motriz, validado experimentalmente, que incluye la dinámica longitudinal del vehículo, modelos para el motor eléctrico y las baterías, y un modelo de motor de combustión de valores medios. El CO puede utilizarse para tres objetivos distintos: 1. Control aplicado, en caso de que las condiciones de contorno estén definidas. Puede aplicarse al control del motor de combustión para un ciclo de conducción dado, traduciéndose en un problema matemático de grandes dimensiones. Se estudian dos casos particulares: la gestión de un sistema de EGR de doble lazo, y el control completo del motor, en particular de las consignas de inyección, SOI, EGR y VGT. 2. Obtención de reglas de control cuasi-óptimas, aplicables en casos en los que no todas las perturbaciones se conocen. A este respecto, se analizan el cálculo de calibraciones de motor específicas para un ciclo, y la gestión energética de un vehículo híbrido mediante un control estocástico en bucle cerrado. 3. Empleo de trayectorias de CO como comparativa o referencia para tareas de diseño y mejora, ofreciendo un criterio objetivo. La ley de combustión así como el dimensionado de una planta motriz híbrida se optimizan mediante el uso de CO. Las estrategias de CO han sido aplicadas experimentalmente en los trabajos referentes al motor de combustión, poniendo de manifiesto sus ventajas sustanciales, pero también analizando dificultades y líneas de actuación para superarlas. Los métodos desarrollados en esta Tesis Doctoral son generales y aplicables a otros criterios si se dispone de los modelos adecuados.El Control Òptim (CO) és essencialment un problema matemàtic de cerca d'extrems, que consisteix en la definició d'un criteri a minimitzar (o maximitzar), restriccions que es deuen satisfer i condicions de contorn que afecten el sistema. La teoria de CO ofereix mètodes per a derivar una trajectòria de control que minimitza (o maximitza) aquest criteri. Aquesta Tesi tracta l'aplicació del CO en automoció i especialment al motor de combustió interna. Les ferramentes necessàries són un mètode d'optimització i una representació matemàtica de la planta motriu. Per a això, es realitza una anàlisi quantitatiu dels avantatges i inconvenients dels tres mètodes d'optimització existents a la literatura: programació dinàmica, principi mínim de Pontryagin i mètodes directes. Es desenvolupen i descriuen els algoritmes per a implementar aquests mètodes així com un model de planta motriu, validat experimentalment, que inclou la dinàmica longitudinal del vehicle, models per al motor elèctric i les bateries, i un model de motor de combustió de valors mitjans. El CO es pot utilitzar per a tres objectius diferents: 1. Control aplicat, en cas que les condicions de contorn estiguen definides. Es pot aplicar al control del motor de combustió per a un cicle de conducció particular, traduint-se en un problema matemàtic de grans dimensions. S'estudien dos casos particulars: la gestió d'un sistema d'EGR de doble llaç, i el control complet del motor, particularment de les consignes d'injecció, SOI, EGR i VGT. 2. Obtenció de regles de control quasi-òptimes, aplicables als casos on no totes les pertorbacions són conegudes. A aquest respecte, s'analitzen el càlcul de calibratges específics de motor per a un cicle, i la gestió energètica d'un vehicle híbrid mitjançant un control estocàstic en bucle tancat. 3. Utilització de trajectòries de CO com comparativa o referència per a tasques de disseny i millora, oferint un criteri objectiu. La llei de combustió així com el dimensionament d'una planta motriu híbrida s'optimitzen mitjançant l'ús de CO. Les estratègies de CO han sigut aplicades experimentalment als treballs referents al motor de combustió, manifestant els seus substancials avantatges, però també analitzant dificultats i línies d'actuació per superar-les. Els mètodes desenvolupats a aquesta Tesi Doctoral són generals i aplicables a uns altres criteris si es disposen dels models adequats.Reig Bernad, A. (2017). Optimal Control for Automotive Powertrain Applications [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90624TESI

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors’ latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK

CAE - PROCESS AND NETWORK : A methodology for continuous product validation process based on network of various digital simulation methods

CAE ProNet methodology is to develop CAE network considering interdependencies among digital validations. Utilizing CAE network and considering industrial requirements, an algorithm is applied to execute a product, vehicle development phase, and load case priority oriented CAE process. Major advantage of this research work is to improve quality of simulation results, reducing time-to-market and decreasing dependencies on hardware prototype

Powertrain Assembly Lines Automatic Configuration Using a Knowledge Based Engineering Approach

Technical knowledge and experience are intangible assets crucial for competitiveness. Knowledge is particularly important when it comes to complex design activities such as the configuration of manufacturing systems. The preliminary design of manufacturing systems relies significantly on experience of designers and engineers, lessons learned and complex sets of rules and is subject to a huge variability of inputs and outputs and involves decisions which must satisfy many competing requirements. This complicated design process is associated with high costs, long lead times and high probability of risks and reworks. It is estimated that around 20% of the designer’s time is dedicated to searching and analyzing past available knowledge, while 40% of the information required for design is identified through personally stored information. At a company level, the design of a new production line does not start from scratch. Based on the basic requirements of the customers, engineers use their own knowledge and try to recall past layout ideas searching for production line designs stored locally in their CAD systems [1]. A lot of knowledge is already stored, and has been used for a long time and evolved over time. There is a need to retrieve this knowledge and integrate it into a common and reachable framework. Knowledge Based Engineering (KBE) and knowledge representation techniques are considered to be a successful way to tackle this design problem at an industrial level. KBE is, in fact, a research field that studies methodologies and technologies for capturing and re-using product and process engineering knowledge to achieve automation of repetitive design tasks [2]. This study presents a methodology to support the configuration of powertrain assembly lines, reducing design times by introducing a best practice for production systems provider companies. The methodology is developed in a real industrial environment, within Comau S.p.A., introducing the role of a knowledge engineer. The approach includes extraction of existing technical knowledge and implementation in a knowledge-based software framework. The macro system design requirements (e.g. cycle time, production mix, etc.) are taken as input. A user driven procedure guides the designer in the definition of the macro layout-related decisions and in the selection of the equipment to be allocated within the project. The framework is then integrated with other software tools allowing the first phase design of the line including a technical description and a 2D and 3D CAD line layout. The KBE application is developed and tested on a specific powertrain assembly case study. Finally, a first validation among design engineers is presented, comparing traditional and new approach and estimating a cost-benefit analysis useful for future possible KBE implementations

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems

Power transmission systems: from traditional to magnetic gearboxes

L'abstract è presente nell'allegato / the abstract is in the attachmen

CAE - PROCESS AND NETWORK : A methodology for continuous product validation process based on network of various digital simulation methods

CAE ProNet methodology is to develop CAE network considering interdependencies among digital validations. Utilizing CAE network and considering industrial requirements, an algorithm is applied to execute a product, vehicle development phase, and load case priority oriented CAE process. Major advantage of this research work is to improve quality of simulation results, reducing time-to-market and decreasing dependencies on hardware prototype

STUDY OF STRATEGIES FOR AN OPTIMAL ENERGY MANAGEMENT ON ELECTRIC AND HYBRID VEHICLES

Questa tesi di dottorato è focalizzata sull’identificazione di strategie di gestione dell’energia a bordo di veicoli elettrici e ibridi, con l’obiettivo di ottimizzare la gestione dell’energia e, quindi, consentire un risparmio di risorse. Infatti, l’ottimizzazione della fase d’uso del veicolo, attraverso una più efficiente gestione dell’energia, consente di dimensionare in modo ridotto i principali componenti, come il pacco batterie. Innanzitutto, viene presentato un tool di simulazione denominato TEST (Target-speed EV Simulation Tool). Questo strumento consente di effettuare simulazioni di dinamica longitudinale per veicoli completamente elettrici o ibridi e, quindi, di monitorare tutti i dati rilevanti necessari per effettuare un corretto dimensionamento del gruppo propulsore, inclusi il/i motore/i elettrico/i ed il pacco batterie. Inoltre, è possibile testare anche diversi layout di propulsori, compresi quelli che utilizzano celle a combustibile, le cosiddette “fuel cell”. Viene poi presentata una strategia di frenata rigenerativa, adatta per veicoli FWD, RWD e AWD. L’obiettivo principale è quello di recuperare la massima energia frenante possibile, mantenendo il veicolo stabile, con buone prestazioni in frenata. La strategia è stata testata sia attraverso un consolidato software di simulazione della dinamica del veicolo (VI-CarRealTime), sia attraverso simulazioni “driver-in-the-loop” utilizzando un simulatore di guida. Inoltre, la strategia proposta è stata integrata nel tool TEST per valutarne l’influenza sull’autonomia e sui consumi del veicolo. Gli strumenti sopra menzionati sono stati utilizzati per studiare uno scenario di casi reali, per valutare la fattibilità dell’utilizzo di una flotta alimentata a fuel cell a metano per svolgere attività di raccolta rifiuti porta a porta. I risultati mostrano un’elevata fattibilità in termini di autonomia del veicolo rispetto alle missioni standard di raccolta dei rifiuti, a condizione che i componenti siano adeguatamente dimensionati. Il dimensionamento dei componenti è stato effettuato attraverso iterazioni, utilizzando diversi componenti nelle stesse missioni. Infine, è stata riportata un’analisi approfondita degli studi LCA (Life Cycle Assessment) relativi ai veicoli elettrici, con particolare attenzione al pacco batterie, evidenziando alcune criticità ambientali. Questo studio sull’LCA sottolinea quindi l’importanza di una corretta gestione dell’energia per ridurre al minimo l’impatto ambientale associato al consumo stesso di energia.This PhD thesis is focused on identifying energy management strategies on board electric and hybrid vehicles, to optimize energy management and thus allow for resource savings. In fact, vehicle’s operational phase optimisation through a more efficient energy management allows main components downsizing, such as battery pack. First of all, a simulation tool called TEST (Target-speed EV Simulation Tool), is presented. This tool allows to carry out longitudinal dynamics simulations on pure electric or hybrid-electric vehicles, and therefore monitoring all the relevant data needed to carry out a proper powertrain sizing, including the electric motor(s) and the battery pack. Furthermore, several powertrain layouts can be also tested, including those using fuel cells. Then a regenerative braking strategy, suitable for FWD, RWD and AWD vehicles, is presented. Its main target is to recover the maximum possible braking energy, while keeping the vehicle stable with good braking performance. The strategy has been tested both through a state-of-art vehicle dynamics simulation software (VI-CarRealTime) and through driver-in-the-loop simulations using a driving simulator. Furthermore, the proposed strategy has been integrated into TEST to evaluate its influence on vehicle range and consumptions. The above-mentioned tools have been used to evaluate a real-world case scenario to assess the feasibility of using a methane fuel cell powered fleet to carry out door to door waste collection activities. Results show high feasibility in terms of vehicle range compared to standard waste collection missions, provided that components are properly sized. Components sizing has been done through iterations using different components on the same missions. Finally, an in-depth analysis of the LCA (Life Cycle Assessment) studies related to electric vehicles has been reported, with particular focus to the battery pack, highlighting some environmental critical issues. This LCA study therefore emphasizes the importance of a correct energy management to minimize the environmental impact associated with energy consumption