29,138 research outputs found

    Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

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    The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

    Ultra Low Carbon Vehicles: New Parameters for Automotive Design

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    As the influence of vehicle emissions on our environment has become better understood, the UK government has recently placed urgent emphasis on the implementation of low carbon technologies in the automotive industry through: the UK Low Carbon Industrial Strategy. The overall objective is to offer big incentives to consumers and support for the development of infrastructure and engineering solutions. This scheme however does not consider how the development of functional and experiential user value might drive consumer demand, contributing to the adoption of low carbon vehicles (LCVs) in the mass market. With the emergence of the North East of England as the UK’s first specialised region for the development of ultra-low carbon vehicles (ULCVs), ONE North East, as a development agency for the region's economic and business development, and Northumbria University Ideas-lab have supported a project to facilitate innovation through the collaboration of technology, research and development (R&D) and business. The High Value Low Carbon (HVLC) project aims to envisage new user value made possible by the integration of low carbon vehicle platforms with new process and network technologies. The HVLC consortium represents vehicle manufacturers and their suppliers as well as technology based companies and through an ongoing process of design concept generation the project offers a hub for innovation led enterprise. Whilst new technological developments in areas such as power generation, nano materials, hydrogen fuel cells, printed electronics and networked communications will all impact on future automotive design, the mass adoption of low carbon technologies represents a paradigm shift for the motorist. This paper aims to describe how the mapping of new parameters will lead to new transport scenarios that will create the space for new collaborative research on user experiences supported by innovative technologies and related services

    Networking Innovation in the European Car Industry : Does the Open Innovation Model Fit?

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    The automobile industry is has entered an innovation race. Uncertain technological trends, long development cycles, highly capital intensive product development, saturated markets, and environmental and safety regulations have subjected the sector to major transformations. The technological and organizational innovations related to these transformations necessitate research that can enhance our understanding of the characteristics of the new systems and extrapolate the implications for companies as well as for the wider economy. Is the industry ready to change and accelerate the pace of its innovation and adaptability? Have the traditional supply chains transformed into supply networks and regional automobile ecosystems? The study investigates the applicability of the Open Innovation concept to a mature capital-intensive asset-based industry, which is preparing for a radical technological discontinuity - the European automobile industry - through interviewing purposely selected knowledgeable respondents across seven European countries. The findings contribute to the understanding of the OI concept by identifying key obstacles to the wider adoption of the OI model, and signalling the importance of intermediaries and large incumbents for driving network development and OI practices as well as the need of new competencies to be developed by all players.Peer reviewe

    Meta-heuristic algorithms in car engine design: a literature survey

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    Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

    A novel topology of high-speed SRM for high-performance traction applications

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    A novel topology of high-speed Switched Reluctance Machine (SRM) for high-performance traction applications is presented in this article. The target application, a Hybrid Electric Vehicle (HEV) in the sport segment poses very demanding specifications on the power and torque density of the electric traction machine. After evaluating multiple alternatives, the topology proposed is a 2-phase axial flux machine featuring both segmented twin rotors and a segmented stator core. Electromagnetic, thermal and mechanical models of the proposed topology are developed and subsequently integrated in an overall optimisation algorithm in order to find the optimal geometry for the application. Special focus is laid on the thermal management of the machine, due to the tough thermal conditions resulting from the high frequency, high current and highly saturated operation. Some experimental results are also included in order to validate the modelling and simulation results

    Development and performance evaluation of a prototype electric hybrid powertrain system for automotive applications

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    Researchers at Universiti Teknologi Malaysia (UTM) have developed a dedicated hybrid power plant based on the parallel configuration using a gasoline engine coupled to a high performance electric motor, specifically targeted for automotive application. The aims are to achieve even lower exhaust emissions, better fuel economy and better performance than the conventional arrangement, demonstrating an alternative solution to the conventional power plant. The engine used is a 1.3 litre spark-ignition, coupled with a 27.5 kW Nexus electric motor. The control strategy developed in conjunction with the program is to use the electric drive motor for initial acceleration and for regeneration braking energy recovery, and for reducing the peak load and transients seen by the engine. A relatively small pack of advanced lead acid batteries is use for energy storage. The design, development and evaluation exercises are fully described giving a comprehensive insight of the prototype and its capabilities
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