Date: Wednesday 11 March 2020
Time: 11:00 - 12:30
Location / Room: Berlioz
Chair:
Selma Saidi, TU Dortmund, DE
Co-Chair:
Donghwa Shin, Soongsil University, KR
This session presents four papers dealing with various aspects of smart automotive and energy systems, including safety and efficiency of photovoltaic panels, deterministic execution behavior of adaptive automotive applications, efficient implementation of fail-operational automated vehicles, and efficient resource usage in networked automotive systems.
| Time | Label | Presentation Title Authors |
|---|---|---|
| 11:00 | 6.7.1 | A DIODE-AWARE MODEL OF PV MODULES FROM DATASHEET SPECIFICATIONS Speaker: Sara Vinco, Politecnico di Torino, IT Authors: Sara Vinco, Yukai Chen, Enrico Macii and Massimo Poncino, Politecnico di Torino, IT Abstract Semi-empirical models of photovoltaic (PV) modulesbased only on datasheet information are popular in electricalenergy systems (EES) simulation because they can be built without measurements and allow quick exploration of alternative devices. One key limitation of these models, however, is the fact that they cannot model the presence of bypass diodes, which are inserted across a set of series-connected cells in a PV moduleto mitigate the impact of partial shading; datasheet information refer in fact to the operations of the module under uniform irradiance. Neglecting the effect of bypass diodes may incur insignificant underestimation of the extracted power. This paper proposes a semi-empirical model for a PV module, that, by taking into account the only available information about bypass diodes in a datasheet, i.e., its number, by a first downscaling the model to a single PV cell and a subsequent upscaling to the level of a substring and of a module, allows to take into accout the diode effect as much accurately as allowed by the datasheet information. Experimental results show that, in a typical PV array on a roof, using a diode-agnostic model can signifantly underestimate the output power production Download Paper (PDF; Only available from the DATE venue WiFi) |
| 11:30 | 6.7.2 | ACHIEVING DETERMINISM IN ADAPTIVE AUTOSAR Speaker: Christian Menard, TU Dresden, DE Authors: Christian Menard1, Andres Goens1, Marten Lohstroh2 and Jeronimo Castrillon1 1TU Dresden, DE; 2University of California, Berkeley, US Abstract AUTOSAR Adaptive Platform is an emerging industry standard that tackles the challenges of modern automotive software design, but does not provide adequate mechanisms to enforce deterministic execution. This poses profound challenges to testing and maintenance of the application software, which is particularly problematic for safety-critical applications. In this paper, we analyze the problem of nondeterminism in AP and propose a framework for the design of deterministic automotive software that transparently integrates with the AP communication mechanisms. We illustrate our approach in a case study based on the brake assistant demonstrator application that is provided by the AUTOSAR consortium. We show that the original implementation is nondeterministic and discuss a deterministic solution based on our framework. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:00 | 6.7.3 | A FAIL-SAFE ARCHITECTURE FOR AUTOMATED DRIVING Speaker: Sebastian vom Dorff, DENSO Automotive Deutschland GmbH, DE Authors: Sebastian vom Dorff1, Bert Böddeker2, Maximilian Kneissl1 and Martin Fränzle3 1DENSO Automotive Deutschland GmbH, DE; 2Autonomous Intelligent Driving GmbH, DE; 3Carl von Ossietzky University Oldenburg, DE Abstract The development of autonomous vehicles has gained a rapid pace. Along with the promising possibilities of such automated systems, the question of how to ensure their safety arises. With increasing levels of automation the need for fail-operational systems, not relying on a back-up driver, poses new challenges in system design. In this paper we propose a lightweight architecture addressing the challenge of a verifiable, fail-safe safety implementation for trajectory planning. It offers a distributed design and the ability to comply with the requirements of ISO26262, while avoiding an overly redundant set-up. Furthermore, we show an example with low-level prediction models applied to a real world situation. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:15 | 6.7.4 | PRIORITY-PRESERVING OPTIMIZATION OF STATUS QUO ID-ASSIGNMENTS IN CONTROLLER AREA NETWORK Speaker: Lea Schoenberger, TU Dortmund University, DE Authors: Sebastian Schwitalla1, Lea Schönberger1 and Jian-Jia Chen2 1TU Dortmund University, DE; 2TU Dortmund, DE Abstract Controller Area Network (CAN) is the prevailing solution for connecting multiple electronic control units (ECUs) in automotive systems. Every broadcast message on the bus is received by each bus participant and introduces computational overhead to the typically resource-constrained ECUs due to interrupt handling. To reduce this overhead, hardware message filters can be applied. However, since such filters are configured according to the message identifiers (IDs) specified in the system, the filter quality is limited by the nature of the ID-assignment. Although hardware message filters are highly relevant for industrial applications, so far, only the optimization of the filter design, but not the related optimization of ID-assignments has been addressed in the literature. In this work, we explicitly focus on the optimization of message ID-assignments against the background of hardware message filtering. More precisely, we propose an optimization algorithm transforming a given ID-assignment in such a way that, based on the resulting IDs, the quality of hardware message filters is improved significantly, i.e., the computational overhead introduced to each ECU is minimized, and, moreover, the priority order of the system remains unchanged. Conducting comprehensive experiments on automotive benchmarks, we show that our proposed algorithm clearly outperforms optimizations based on the conventional method simulated annealing with respect to the achieved filter quality as well as to the runtime. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:30 | IP3-7, 519 | APPLYING RESERVATION-BASED SCHEDULING TO A µC-BASED HYPERVISOR: AN INDUSTRIAL CASE STUDY Speaker: Dirk Ziegenbein, Robert Bosch GmbH, DE Authors: Dakshina Dasari1, Paul Austin2, Michael Pressler1, Arne Hamann1 and Dirk Ziegenbein1 1Robert Bosch GmbH, DE; 2ETAS GmbH, GB Abstract Existing software scheduling mechanisms do not suffice for emerging applications in the automotive space, which have the conflicting needs of performance and predictability. %We need mechanisms that lend themselves naturally to this requirement, by virtue of their design. As a concrete case, we consider the ETAS light-weight hypervisor, a commercially viable solution in the automotive industry, deployed on multicore microcontrollers. We describe the architecture of the hypervisor and its current scheduling mechanisms based on Time Division Multiplexing. We next show how Reservation-based Scheduling can be implemented in the ETAS LWHVR to efficiently use resources while also providing freedom from interference and explore design choices towards an efficient implementation of such a scheduler. With experiments from an industry use case, we also compare the performance of RBS and the existing scheduler in the hypervisor. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:31 | IP3-8, 353 | REAL-TIME ENERGY MONITORING IN IOT-ENABLED MOBILE DEVICES Speaker: Nitin Shivaraman, TUMCREATE, SG Authors: Nitin Shivaraman1, Seima Suriyasekaran1, Zhiwei Liu2, Saravanan Ramanathan1, Arvind Easwaran2 and Sebastian Steinhorst3 1TUMCREATE, SG; 2Nanyang Technological University, SG; 3TU Munich, DE Abstract With rapid advancements in the Internet of Things (IoT) paradigm, every electrical device in the near future is expected to have IoT capabilities. This enables fine-grained tracking of individual energy consumption data of such devices, offering location-independent per-device billing and demand management. Hence, it abstracts from the location-based metering of state-of-the-art infrastructure, which traditionally aggregates on a building or household level, defining the entity to be billed. However, such in-device energy metering is susceptible to manipulation and fraud. As a remedy, we propose a secure decentralized metering architecture that enables devices with IoT capabilities to measure their own energy consumption. In this architecture, the device-level consumption is additionally reported to a system-level aggregator that verifies distributed information from our decentralized metering systems and provides secure data storage using Blockchain, preventing data manipulation by untrusted entities. Through experimental evaluation, we show that the proposed architecture supports device mobility and enables location-independent monitoring of energy consumption. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:30 | End of session | |