3,927 research outputs found
Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility
The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehicles’ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicle’s technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehicles’ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.publishedVersio
INCOBAT
Electro-mobility is considered as a key technology to achieve green mobility and fulfil tomorrow’s emission standards. However, different challenges still need to be faced to achieve comparable performances to conventional vehicles and finally obtain market acceptance. Two of these challenges are vehicle range and production costs. In that context, the aim of INCOBAT (October 2013 – December 2016) was to provide innovative and cost efficient battery management systems for next generation HV-batteries. INCOBAT proposes a platform concept that achieves cost reduction, reduced complexity, increased reliability and flexibility while at the same time reaching higher energy efficiency.• Very tight control of the cell function leading to a significant increase of the driving range of the FEV;• Radical cost reduction of the battery management system with respect to current solutions;• Development of modular concepts for system architecture and partitioning, safety, security, reliability as well as verification and validation, thus enabling efficient integration into different vehicle platforms. The INCOBAT project focused on the following twelve technical innovations grouped into four innovation groups, which are summarized in this book:• Customer needs and integration aspects• Transversal innovation• Technology innovation• Transversal innovatio
New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs
Tesis por compendio[EN] Relevance of electronics towards safety of common devices has only been growing, as an ever growing stake of the functionality is assigned to them. But of course, this comes along the constant need for higher performances to fulfill such functionality requirements, while keeping power and budget low. In this scenario, industry is struggling to provide a technology which meets all the performance, power and price specifications, at the cost of an increased vulnerability to several types of known faults or the appearance of new ones.
To provide a solution for the new and growing faults in the systems, designers have been using traditional techniques from safety-critical applications, which offer in general suboptimal results. In fact, modern embedded architectures offer the possibility of optimizing the dependability properties by enabling the interaction of hardware, firmware and software levels in the process. However, that point is not yet successfully achieved. Advances in every level towards that direction are much needed if flexible, robust, resilient and cost effective fault tolerance is desired. The work presented here focuses on the hardware level, with the background consideration of a potential integration into a holistic approach.
The efforts in this thesis have focused several issues: (i) to introduce additional fault models as required for adequate representativity of physical effects blooming in modern manufacturing technologies, (ii) to provide tools and methods to efficiently inject both the proposed models and classical ones, (iii) to analyze the optimum method for assessing the robustness of the systems by using extensive fault injection and later correlation with higher level layers in an effort to cut development time and cost, (iv) to provide new detection methodologies to cope with challenges modeled by proposed fault models, (v) to propose mitigation strategies focused towards tackling such new threat scenarios and (vi) to devise an automated methodology for the deployment of many fault tolerance mechanisms in a systematic robust way.
The outcomes of the thesis constitute a suite of tools and methods to help the designer of critical systems in his task to develop robust, validated, and on-time designs tailored to his application.[ES] La relevancia que la electrĂłnica adquiere en la seguridad de los productos ha crecido inexorablemente, puesto que cada vez Ă©sta copa una mayor influencia en la funcionalidad de los mismos. Pero, por supuesto, este hecho viene acompañado de una necesidad constante de mayores prestaciones para cumplir con los requerimientos funcionales, al tiempo que se mantienen los costes y el consumo en unos niveles reducidos. En este escenario, la industria está realizando esfuerzos para proveer una tecnologĂa que cumpla con todas las especificaciones de potencia, consumo y precio, a costa de un incremento en la vulnerabilidad a mĂşltiples tipos de fallos conocidos o la introducciĂłn de nuevos.
Para ofrecer una soluciĂłn a los fallos nuevos y crecientes en los sistemas, los diseñadores han recurrido a tĂ©cnicas tradicionalmente asociadas a sistemas crĂticos para la seguridad, que ofrecen en general resultados sub-Ăłptimos. De hecho, las arquitecturas empotradas modernas ofrecen la posibilidad de optimizar las propiedades de confiabilidad al habilitar la interacciĂłn de los niveles de hardware, firmware y software en el proceso. No obstante, ese punto no está resulto todavĂa. Se necesitan avances en todos los niveles en la mencionada direcciĂłn para poder alcanzar los objetivos de una tolerancia a fallos flexible, robusta, resiliente y a bajo coste. El trabajo presentado aquĂ se centra en el nivel de hardware, con la consideraciĂłn de fondo de una potencial integraciĂłn en una estrategia holĂstica.
Los esfuerzos de esta tesis se han centrado en los siguientes aspectos: (i) la introducciĂłn de modelos de fallo adicionales requeridos para la representaciĂłn adecuada de efectos fĂsicos surgentes en las tecnologĂas de manufactura actuales, (ii) la provisiĂłn de herramientas y mĂ©todos para la inyecciĂłn eficiente de los modelos propuestos y de los clásicos, (iii) el análisis del mĂ©todo Ăłptimo para estudiar la robustez de sistemas mediante el uso de inyecciĂłn de fallos extensiva, y la posterior correlaciĂłn con capas de más alto nivel en un esfuerzo por recortar el tiempo y coste de desarrollo, (iv) la provisiĂłn de nuevos mĂ©todos de detecciĂłn para cubrir los retos planteados por los modelos de fallo propuestos, (v) la propuesta de estrategias de mitigaciĂłn enfocadas hacia el tratamiento de dichos escenarios de amenaza y (vi) la introducciĂłn de una metodologĂa automatizada de despliegue de diversos mecanismos de tolerancia a fallos de forma robusta y sistemática.
Los resultados de la presente tesis constituyen un conjunto de herramientas y mĂ©todos para ayudar al diseñador de sistemas crĂticos en su tarea de desarrollo de diseños robustos, validados y en tiempo adaptados a su aplicaciĂłn.[CA] La rellevĂ ncia que l'electrònica adquireix en la seguretat dels productes ha crescut inexorablement, puix cada volta mĂ©s aquesta abasta una major influència en la funcionalitat dels mateixos. Però, per descomptat, aquest fet ve acompanyat d'un constant necessitat de majors prestacions per acomplir els requeriments funcionals, mentre es mantenen els costos i consums en uns nivells reduĂŻts. Donat aquest escenari, la indĂşstria estĂ fent esforços per proveir una tecnologia que complisca amb totes les especificacions de potència, consum i preu, tot a costa d'un increment en la vulnerabilitat a diversos tipus de fallades conegudes, i a la introducciĂł de nous tipus.
Per oferir una soluciĂł a les noves i creixents fallades als sistemes, els dissenyadors han recorregut a tècniques tradicionalment associades a sistemes crĂtics per a la seguretat, que en general oferixen resultats sub-òptims. De fet, les arquitectures empotrades modernes oferixen la possibilitat d'optimitzar les propietats de confiabilitat en habilitar la interacciĂł dels nivells de hardware, firmware i software en el procĂ©s. Tot i això eixe punt no estĂ resolt encara. Es necessiten avanços a tots els nivells en l'esmentada direcciĂł per poder assolir els objectius d'una tolerĂ ncia a fallades flexible, robusta, resilient i a baix cost. El treball acĂ presentat se centra en el nivell de hardware, amb la consideraciĂł de fons d'una potencial integraciĂł en una estratègia holĂstica.
Els esforços d'esta tesi s'han centrat en els segĂĽents aspectes: (i) la introducciĂł de models de fallada addicionals requerits per a la representaciĂł adequada d'efectes fĂsics que apareixen en les tecnologies de fabricaciĂł actuals, (ii) la provisiĂł de ferramentes i mètodes per a la injecciĂł eficient del models proposats i dels clĂ ssics, (iii) l'anĂ lisi del mètode òptim per estudiar la robustesa de sistemes mitjançant l'Ăşs d'injecciĂł de fallades extensiva, i la posterior correlaciĂł amb capes de mĂ©s alt nivell en un esforç per retallar el temps i cost de desenvolupament, (iv) la provisiĂł de nous mètodes de detecciĂł per cobrir els reptes plantejats pels models de fallades proposats, (v) la proposta d'estratègies de mitigaciĂł enfocades cap al tractament dels esmentats escenaris d'amenaça i (vi) la introducciĂł d'una metodologia automatitzada de desplegament de diversos mecanismes de tolerĂ ncia a fallades de forma robusta i sistemĂ tica.
Els resultats de la present tesi constitueixen un conjunt de ferramentes i mètodes per ajudar el dissenyador de sistemes crĂtics en la seua tasca de desenvolupament de dissenys robustos, validats i a temps adaptats a la seua aplicaciĂł.Espinosa GarcĂa, J. (2016). New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/73146TESISCompendi
Degradation modeling and degradation-aware control of power electronic systems
The power electronics market is valued at 36.64 billion by 2027. Power electronic systems (PES) have been extensively used in a wide range of critical applications, including automotive, renewable energy, industrial variable-frequency drive, etc. Thus, the PESs\u27 reliability and robustness are immensely important for the smooth operation of mission-critical applications. Power semiconductor switches are one of the most vulnerable components in the PES. The vulnerability of these switches impacts the reliability and robustness of the PES. Thus, switch-health monitoring and prognosis are critical for avoiding unexpected shutdowns and preventing catastrophic failures. The importance of the prognosis study increases dramatically with the growing popularity of the next-generation power semiconductor switches, wide bandgap switches. These switches show immense promise in the high-power high-frequency operations due to their higher breakdown voltage and lower switch loss. But their wide adaptation is limited by the inadequate reliability study. A thorough prognosis study comprising switch degradation modeling, remaining useful life (RUL) estimation, and degradation-aware controller development, is important to enhance the PESs\u27 robustness, especially with wide bandgap switches. In this dissertation, three studies are conducted to achieve these objectives- 1) Insulated Gate Bipolar Transistor (IGBT) degradation modeling and RUL estimation, 2) cascode Gallium Nitride (GaN) Field-Effect Transistor (FET) degradation modeling and RUL estimation, and 3) Degradation-aware controller design for a PES, solid-state transformer (SST). The first two studies have addressed the significant variation in RUL estimation and proposed degradation identification methods for IGBT and cascode GaN FET. In the third study, a system-level integration of the switch degradation model is implemented in the SST. The insight into the switch\u27s degradation pattern from the first two studies is integrated into developing a degradation-aware controller for the SST. State-of-the-art controllers do not consider the switch degradation that results in premature system failure. The proposed low-complexity degradation-aware and adaptive SST controller ensures optimal degradation-aware power transfer and robust operation over the lifetime
INCOBAT
Electro-mobility is considered as a key technology to achieve green mobility and fulfil tomorrow’s emission standards. However, different challenges still need to be faced to achieve comparable performances to conventional vehicles and finally obtain market acceptance. Two of these challenges are vehicle range and production costs. In that context, the aim of INCOBAT (October 2013 – December 2016) was to provide innovative and cost efficient battery management systems for next generation HV-batteries. INCOBAT proposes a platform concept that achieves cost reduction, reduced complexity, increased reliability and flexibility while at the same time reaching higher energy efficiency.• Very tight control of the cell function leading to a significant increase of the driving range of the FEV;• Radical cost reduction of the battery management system with respect to current solutions;• Development of modular concepts for system architecture and partitioning, safety, security, reliability as well as verification and validation, thus enabling efficient integration into different vehicle platforms. The INCOBAT project focused on the following twelve technical innovations grouped into four innovation groups, which are summarized in this book:• Customer needs and integration aspects• Transversal innovation• Technology innovation• Transversal innovatio
Thermal Aware Design Automation of the Electronic Control System for Autonomous Vehicles
The autonomous vehicle (AV) technology, due to its tremendous social and economical benefits, is transforming the entire world in the coming decades. However, significant technical challenges still need to be overcome until AVs can be safely, reliably, and massively deployed. Temperature plays a key role in the safety and reliability of an AV, not only because a vehicle is subjected to extreme operating temperatures but also because the increasing computations demand more powerful IC chips, which can lead to higher operating temperature and large thermal gradient. In particular, as the underpinning technology for AV, artificial intelligence (AI) requires substantially increased computation and memory resources, which have been growing exponentially through recent years and further exacerbated the thermal problems. High operating temperature and large thermal gradient can reduce the performance, degrade the reliability, and even cause an IC to fail catastrophically. We believe that dealing with thermal issues must be coupled closely in the design phase of the AVs’ electronic control system (ECS). To this end, first, we study how to map vehicle applications to ECS with heterogeneous architecture to satisfy peak temperature constraints and optimize latency and system-level reliability. We present a mathematical programming model to bound the peak temperature for the ECS. We also develop an approach based on the genetic algorithm to bound the peak temperature under varying execution time scenarios and optimize the system-level reliability of the ECS. We present several computationally efficient techniques for system-level mean-time-to-failure (MTTF) computation, which show several orders-of-magnitude speed-up over the state-of-the-art method. Second, we focus on studying the thermal impacts of AI techniques. Specifically, we study how the thermal impacts for the memory bit flipping can affect the prediction accuracy of a deep neural network (DNN). We develop a neuron-level analytical sensitivity estimation framework to quantify this impact and study its effectiveness with popular DNN architectures. Third, we study the problem of incorporating thermal impacts into mapping the parameters for DNN neurons to memory banks to improve prediction accuracy. Based on our developed sensitivity metric, we develop a bin-packing-based approach to map DNN neuron parameters to memory banks with different temperature profiles. We also study the problem of identifying the optimal temperature profiles for memory systems that can minimize the thermal impacts. We show that the thermal aware mapping of DNN neuron parameters on memory banks can significantly improve the prediction accuracy at a high-temperature range than the thermal ignorant for state-of-the-art DNNs
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