Date: Tuesday 15 March 2016
Time: 11:30 - 13:00
Location / Room: Konferenz 1
Chair:
Geoff Merrett, University of Southampton, GB
Co-Chair:
Frank Hannig, Friedrich-Alexander-Universität Erlangen-Nürnberg, DE
This session considers the state of the art in automotive systems and smart energy systems including novel approaches for efficient embedded software in automobiles, formal analyses and fault detection, and joint optimisation approaches for lifetime and functionality improvements in electric vehicles.
| Time | Label | Presentation Title Authors |
|---|---|---|
| 11:30 | 2.3.1 | (Best Paper Award Candidate) OTEM: OPTIMIZED THERMAL AND ENERGY MANAGEMENT FOR HYBRID ELECTRICAL ENERGY STORAGE IN ELECTRIC VEHICLES Speaker: Mohammad Al Faruque, University of California, Irvine, US Authors: Korosh Vatanparvar and Mohammad Abdullah Al Faruque, University of California, Irvine, US Abstract Electric Vehicles (EV) pose challenges in terms of reliability and performance which are due to the stringent design constraints. For instance, an insufficient energy storage restricts the EV driving range. Highly dense battery packs providing EV with the required power, may generate extreme internal heat which causes the battery temperature to rise significantly and thereby results in reliability and safety issues. Moreover, both high battery utilization and temperature may degrade the battery capacity and Battery LifeTime (BLT), which should be extended as much as possible to postpone expensive battery replacement costs. Although, researchers have provided separate battery energy and thermal managements for EVs to address the above-mentioned challenges, in this paper, we are bringing a joint optimized solution. Hence, we introduce a novel metric Thermal and Energy Budget (TEB) in a Hybrid Electrical Energy Storage (HEES) with an active battery cooling system. Furthermore, we propose a novel Optimized Thermal and Energy Management (OTEM) methodology which optimizes the battery/ultracapacitor utilization, battery temperature, and thereby TEB, in order to improve the driving range, extend the BLT, and maintain the battery temperature in the safe zone. Our methodology provides significant improvement in BLT (on average 16.8%) and average energy consumption (on average 12.1% reduction) compared to the state-of-the-art methodologies. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:00 | 2.3.2 | SUPERTASK: MAXIMIZING RUNNABLE-LEVEL PARALLELISM IN AUTOSAR APPLICATIONS Speaker: Sebastian Kehr, Denso Automotive Deutschland GmbH, DE Authors: Sebastian Kehr1, Milos Panic2, Eduardo Quinones3, Bert Boeddeker1, Jorge Becerril Sandoval1, Jaume Abella3, Francisco Cazorla4 and Günter Schäfer5 1Denso Automotive Deutschland GmbH, DE; 2Barcelona Supercomputing Center and Universitat Politècnica de Catalunya, ES; 3Barcelona Supercomputing Center, ES; 4Barcelona Supercomputing Center and IIIA-CSIC, ES; 5Ilmenau University of Technology, DE Abstract The migration of legacy AUTOSAR automotive software from a single-core ECU to a multicore ECU faces two main challenges: 1) data dependencies between AUTOSAR runnables must be respected, which may limit the level of parallelism; 2) the original data-flow from the single-core must be reproduced, in order to guarantee the same functional behaviour without exhaustive validation and testing efforts afterwards. This article proposes the concept of supertask that maximizes the level of parallelism among runnables and maintains the original data-flow from the single-core. Supertasks group consecutively scheduled AUTOSAR tasks into a unique scheduling entity with a period equal to the least common multiple of tasks composing it. We evaluate supertasks with a real automotive application and compare it with existing state-of-the-art approaches with the same objectives. Our results show that supertasks effectively increase the performance with respect to current state-of-the-art, resulting in an overall performance improvement of the application when combining supertask with current approaches. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:30 | 2.3.3 | FORMAL ANALYSIS BASED EVALUATION OF SOFTWARE DEFINED NETWORKING FOR TIME-SENSITIVE ETHERNET Speaker: Daniel Thiele, Technische Universität Braunschweig, DE Authors: Daniel Thiele and Rolf Ernst, Technische Universität Braunschweig, DE Abstract Software defined networking (SDN) aims to standardize the control and configuration of network infrastructure. It consolidates network control by moving the network's control plane to a (logically) centralized controller and downgrading switches to simple forwarding devices. This offers huge advantages for future automotive Ethernet networks, including admission control (e.g. to prevent/limit congestion) or network reconfiguration (e.g. in case of faults), both based on a centralized view of the current network state. SDN's centralized architecture, however, requires additional communication, which entails a certain overhead. If SDN is used in safety-critical real-time networks, this communication is subject to strict timing requirements. In this paper, we present a formal analysis based evaluation of the general suitability of SDN for time-sensitive networks including overhead, scalability, and timing guarantees by using a realistic automotive setup. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:45 | 2.3.4 | ACCELERATED ARTIFICIAL NEURAL NETWORKS ON FPGA FOR FAULT DETECTION IN AUTOMOTIVE SYSTEMS Speaker: Shreejith Shanker, Nanyang Technological University, SG Authors: Shreejith Shanker1, Bezborah Anshuman1 and Suhaib A. Fahmy2 1Nanyang Technological University, SG; 2University of Warwick, GB Abstract Modern vehicles are complex distributed systems with critical real-time electronic controls that have progressively replaced their mechanical/hydraulic counterparts, for performance and cost benefits. The harsh and varying vehicular environment can induce multiple errors in the computational/communication path, with temporary or permanent effects, thus demanding the use of fault-tolerant schemes. Constraints in location, weight, and cost prevent the use of physical redundancy for critical systems in many cases, such as within an internal combustion engine. Alternatively, algorithmic techniques like artificial neural networks (ANNs) can be used to detect errors and apply corrective measures in computation. Though adaptability of ANNs presents advantages for fault-detection and fault-tolerance measures for critical sensors, implementation on automotive grade processors may not serve required hard deadlines and accuracy simultaneously. In this work, we present an ANN-based fault-tolerance system based on hybrid FPGAs and evaluate it using a diesel engine case study. We show that the hybrid platform outperforms an optimised software implementation on an automotive grade ARM Cortex M4 processor in terms of latency and power consumption, also providing better consolidation. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 13:00 | IP1-1, 56 | A SCALABLE LANE DETECTION ALGORITHM ON COTSS WITH OPENCL Speaker: Kai Huang, Sun Yat-Sen University, CN Authors: Kai Huang1, Biao Hu2, Jan Botsch3, Nikhil Madduri3 and Alois Knoll3 1Sun Yat-Sen University, CN; 2Technische Universität München (TUM), DE; 3Technische Universität München (TUM), DE Abstract Road lane detection are classical requirements for advanced driving assistant systems. With new computer technologies, lane detection algorithms can be exploited on Cots platforms. This paper investigates the use of OpenCL and develop a particle- filter based lane detection algorithm that can tune the trade-off between detection accuracy and speed. Our algorithm is tested on 14 video streams from different data-sets with different scenarios on different Cots hardware. With an average deviation fewer than 5 pixels, the average frame rates for the 14 videos can reach about 400 fps on both Gpu and Fpga. The peak frame rates for certain videos on GPU can reach almost 1000 fps. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 13:01 | IP1-2, 611 | SIMULATION OF FALLING RAIN FOR ROBUSTNESS TESTING OF VIDEO-BASED SURROUND SENSING SYSTEMS Speaker: Dennis Hospach, Universität Tübingen, DE Authors: Dennis Hospach1, Stefan Mueller1, Wolfgang Rosenstiel1 and Oliver Bringmann2 1Universität Tübingen, DE; 2Universität Tübingen / FZI, DE Abstract Recently, optical sensors have become a standard item in modern cars, raising questions with respect to the necessary testing under various ambient effects. In order to achieve a high test coverage of vision-based surround sensing systems, a lot of different environmental conditions need to be tested. Unfortunately, it is by far too time-consuming to build test sets of all relevant environmental conditions by recording real video data. This paper presents a novel approach for ambient-aware virtual prototyping and robustness testing. We propose a method to significantly reduce the needed on-road captures being used for design and validation of vision-based Advanced Driver Assistance Systems (ADAS) and fully automated driving. Our approach facilitates the generation of comparable test sets by using largely reduced amounts of real on-road captures and applying computer-generated variations of falling rain to it in a comprehensive virtual prototyping environment. In combination with the simulation of camera properties, which influence the visual effects of falling rain to a great extent, we are able to generate different rain scenarios under a wide variety of parameters. Our approach has been applied to an automotive lane detection system using a series of multiple rain scenarios. We have explored, how falling rain can influence such a system and how such behavior can be detected using simulated rain scenarios. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 13:02 | IP1-3, 618 | PROPOSAL FOR FAST DIRECTIONAL ENERGY INTERCHANGE USED IN MCMC-BASED AUTONOMOUS DECENTRALIZED MECHANISM TOWARD RESILIENT MICROGRID Speaker: Yusuke Sakumoto, Tokyo Metropolitan University, JP Authors: Yusuke Sakumoto1 and Ittetsu Taniguchi2 1Tokyo Metropolitan University, JP; 2Ritsumeikan University, JP Abstract Microgrid is well known as key technology to improve renewable energy's ease of use. Some previous works focused on a microgrid that is divided into autonomous electricity subsystems~(AESs) for its reliability and scalability. We have proposed the MCMC-based autonomous decentralized mechanism (ADM) to perform energy interchange between AESs so as to be supply energy appropriately for different energy demands among AESs. In this paper, toward resilient of microgrids, we design a method to realize directional energy interchange in our ADM on the basis of the convection diffusion. We investigate the effectiveness of the proposed method through simulation experiment considering energy shortage and emergency situations. We clarify that the proposed method can fast supply energy from external power grid to a microgrid under energy shortage situation, and can fast gather distributed energy to a specific AES~(e.g., safe shelter) under emergency situation. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 13:00 | End of session Lunch Break in Großer Saal + Saal 1 |