Fast data based identification of thermal vehicle models for integrated powertrain control

2021 ◽  
Author(s):  
Florian Meier ◽  
Daniel Adelberger ◽  
Luigi del Re
Keyword(s):  
Powertrain Control

Research on highly parallel embedded control system design and implementation method

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 44-46
Author(s):  
Masato Edahiro ◽  
Masaki Gondo
Keyword(s):  
Computer Architecture ◽  
Intelligent Systems ◽  
Large Scale ◽  
General Purpose ◽  
Heterogeneous Structure ◽  
Single Chip ◽  
Powertrain Control ◽  
Processing Power ◽  
Hardware Description ◽  
Many Core

The pace of technology's advancements is ever-increasing and intelligent systems, such as those found in robots and vehicles, have become larger and more complex. These intelligent systems have a heterogeneous structure, comprising a mixture of modules such as artificial intelligence (AI) and powertrain control modules that facilitate large-scale numerical calculation and real-time periodic processing functions. Information technology expert Professor Masato Edahiro, from the Graduate School of Informatics at the Nagoya University in Japan, explains that concurrent advances in semiconductor research have led to the miniaturisation of semiconductors, allowing a greater number of processors to be mounted on a single chip, increasing potential processing power. 'In addition to general-purpose processors such as CPUs, a mixture of multiple types of accelerators such as GPGPU and FPGA has evolved, producing a more complex and heterogeneous computer architecture,' he says. Edahiro and his partners have been working on the eMBP, a model-based parallelizer (MBP) that offers a mapping system as an efficient way of automatically generating parallel code for multi- and many-core systems. This ensures that once the hardware description is written, eMBP can bridge the gap between software and hardware to ensure that not only is an efficient ecosystem achieved for hardware vendors, but the need for different software vendors to adapt code for their particular platforms is also eliminated.

scholarly journals Benchmark of Rotor Position Sensor Technologies for Application in Automotive Electric Drive Trains

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1063 ◽  
Author(s):  
Christoph Datlinger ◽  
Mario Hirz
Keyword(s):  
Evaluation Criteria ◽  
Position Sensor ◽  
Permanent Magnet Synchronous Machines ◽  
Rotor Position ◽  
Powertrain Control ◽  
Alternative Technologies ◽  
Traction Motors ◽  
Drive Trains ◽  
Automotive Powertrain ◽  
Electric Powertrains

Rotor shaft position sensors are required to ensure the efficient and reliable control of Permanent Magnet Synchronous Machines (PMSM), which are often applied as traction motors in electrified automotive powertrains. In general, various sensor principles are available, e.g., resolvers and inductive- or magnetoresistive sensors. Each technology is characterized by strengths and weaknesses in terms of measurement accuracy, space demands, disturbing factors and costs, etc. Since the most frequently applied technology, the resolver, shows some weaknesses and is relatively costly, alternative technologies have been introduced during the past years. This paper investigates state-of-the-art position sensor technologies and compares their potentials for use in PMSM in automotive powertrain systems. The corresponding evaluation criteria are defined according to the typical requirements of automotive electric powertrains, and include the provided sensor accuracy under the influence of mechanical tolerances and deviations, integration size, and different electrical- and signal processing-related parameters. The study presents a mapping of the potentials of different rotor position sensor technologies with the target to support the selection of suitable sensor technologies for specified powertrain control applications, addressing both system design and components development.

scholarly journals Progress on Powertrain Verification Challenge with C2E2

10.29007/1kq2 ◽  
2018 ◽  
Author(s):  
Chuchu Fan ◽  
Parasara Sridhar Duggirala ◽  
Sayan Mitra ◽  
Mahesh Viswanathan
Keyword(s):  
Rate Of Convergence ◽  
Control Systems ◽  
Hybrid System ◽  
State Machines ◽  
Powertrain Control ◽  
Verification Tool ◽  
Discrepancy Rate ◽  
System Verification ◽  
Made In

In this paper, we present the progress we have made in verifying the benchmark powertrain control systems introduced in the last ARCH workshop. We implemented the algorithm for computing local discrepancy (rate of convergence or divergence of trajectories) reported in the hybrid system verification tool C2E2. We created Stateflow translations of the original models to aid the processing using C2E2 tool. We also had to encode the different driver behaviors in the form of state machines. With these customizations, we have been successful in verifying one of the easier (but still challenging) benchmarks from the powertrain suite. In this paper, we present some of the engineering challenges and describe the artifacts we created in the process.

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