Browsing by Keyword "System-on-chip"
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Item Multi motor electric powertrains: Technological potential and implementation of a model based approach(IEEE Computer Society, 2016-12-21) Dendaluce Jahnke, Martin; Allende Marcos, Miguel; Pérez Rastelli, Joshué; Prieto Arce, Pablo; Martin Sandi, Adrián; Tecnalia Research & Innovation; CCAM; POWERTRAINVehicle electrification is proliferating and evolving towards multi-motor vehicles. This implies new degrees of freedom and higher controllability. Meanwhile, embedded technology is presenting attractive new solutions. Furthermore, Model-Based Development gains relevance as the complexity of automotive applications continues to grow and regulations address functional safety. The implications of this context are described in this work and taken as motivation to implement a solution that involves the key technologies related to the discussed domains and their remarkable potential. This paper presents the implementation of a methodology and its workflow with a toolchain setup which has been used to develop and commission a System-on-Chip-based ECU for a Torque Vectoring algorithm in a Motor-in-Wheel demonstrator vehicle. The implemented solution permits to rapidly and safely move from algorithm development and laboratory simulations to real circuit testing, agilely iterating control enhancements, tests and validation, for an efficient and effective deployment. Furthermore, both the applied methodology and the selected toolchain are suited for future certification considerations.Item System-on-chip-based highly integrated powertrain control unit for next-generation electric vehicles: Harnessing the potential of hybrid embedded platforms for advanced model-based control algorithms(Korean Society of Automotive Engineers, 2015) Dendaluce, M.; Tecnalia Research & InnovationIn this paper, a novel highly integrated System on Chip (SoC) based control unit concept is presented, which is conceived to combine the functionality of various powertrain ECUs and to additionally enhance their control with predictions based on the real-time execution of complex mathematical models. Such a platform has the potential for providing considerable benefits to upcoming hybrid and electric vehicles, especially for highly complex and efficient hybrid and multi-motor electric vehicles. A clear advantage is the reduction of Control Units, consequently also reducing the system complexity, communication requirements and development effort, which are directly associated to production and development costs. A controller architecture capable of exploiting the strength intrinsic to the nature of each platform type is presented, basing on the new generation of high-performance hybrid SoC platforms which combine powerful processors with cutting edge FPGAS. The parallel hardware paradigm of FPGAS enables the implementation into a single component not only of several Field Oriented Control loops for electrical motors, power management functions and vehicle-level optimizations, but also of advanced real-time predictive algorithms. The combination of so many complex tasks would not be feasible on a typical automotive microcontroller unit. A further objective for obtaining a highly integrated solution is to establish an efficient development and prototyping process, aiming to simplify and harmonize the workflow through the whole V model, by completely basing it on model-based-design tools. Finally, the concept demonstrator being implemented in this paper will combine a state-of-the-art high performance microprocessor and FPGA using a commercial SoC platform together with model-based software development tools. This will also fulfil the expectation of providing a topology with great migration and industrialization potential for the case of higher qualification requirements. Furthermore, it is another step towards a necessary mindset shift on control system development and integration methods for increasingly complex vehicles.