Simulation-based development of automotive control software with Modelica

Chrisofakis, Emmanuel; Junghanns, Andreas; Kehrer, Christian; Rink, Anton

doi:10.3384/ecp110631

Cited by 17 publications

(9 citation statements)

References 1 publication

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“…Alternatively, debugging methods have been studied in Software-in-the-Loop (SiL) environments in which the source code is available [17,18]. A development process has been proposed for system integration in an SiL environment that can save system-development time and cost [17].…”

Section: Testing and Debugging Methods For Automotive Ecusmentioning

confidence: 99%

“…A development process has been proposed for system integration in an SiL environment that can save system-development time and cost [17]. Another method is to model automotive software using the Modelica tool, and to debug by connecting an external debugger to an SiL environment running the simulation [18]. However, since these methods cannot be applied to automotive ECU debugging in an environment where the source code is unavailable, a method that can generate fault-location information in a black-box environment is still required.…”

Section: Testing and Debugging Methods For Automotive Ecusmentioning

confidence: 99%

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Fault Localization Method by Partitioning Memory Using Memory Map and the Stack for Automotive ECU Software Testing

2016

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Abstract:Recently, the usage of the automotive Electronic Control Unit (ECU) and its software in cars is increasing. Therefore, as the functional complexity of such software increases, so does the likelihood of software-related faults. Therefore, it is important to ensure the reliability of ECU software in order to ensure automobile safety. For this reason, systematic testing methods are required that can guarantee software quality. However, it is difficult to locate a fault during testing with the current ECU development system because a tester performs the black-box testing using a Hardware-in-the-Loop (HiL) simulator. Consequently, developers consume a large amount of money and time for debugging because they perform debugging without any information about the location of the fault. In this paper, we propose a method for localizing the fault utilizing memory information during black-box testing. This is likely to be of use to developers who debug automotive software. In order to observe whether symbols stored in the memory have been updated, the memory is partitioned by a memory map and the stack, thus the fault candidate region is reduced. A memory map method has the advantage of being able to finely partition the memory, and the stack method can partition the memory without a memory map. We validated these methods by applying these to HiL testing of the ECU for a body control system. The preliminary results indicate that a memory map and the stack reduce the possible fault locations to 22% and 19% of the updated memory, respectively.

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Section: Testing and Debugging Methods For Automotive Ecusmentioning

confidence: 99%

Section: Testing and Debugging Methods For Automotive Ecusmentioning

confidence: 99%

Fault Localization Method by Partitioning Memory Using Memory Map and the Stack for Automotive ECU Software Testing

2016

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“…In all new gearbox projects for Mercedes-Benz passenger cars FMI is used for software-in-the-loop simulations [3]. Control software and FMUs coming from different modeling environments run in closedloop in the virtual ECU tool Silver on Windows PC in order to validate, test and debug control software.…”

Section: Fmi Usagementioning

confidence: 99%

Functional Mockup Interface 2.0: The Standard for Tool independent Exchange of Simulation Models

Blochwitz¹,

Otter²,

Åkesson³

et al. 2012

Linköping Electronic Conference Proceedings

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410

224

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The Functional Mockup Interface (FMI) is a tool independent standard for the exchange of dynamic models and for Co-Simulation. The first version, FMI 1.0, was published in 2010. Already more than 30 tools support FMI 1.0. In this paper an overview about the upcoming version 2.0 of FMI is given that combines the formerly separated interfaces for Model Exchange and Co-Simulation in one standard. Based on the experience on using FMI 1.0, many small details have been improved and new features introduced to ease the use and increase the performance especially for larger models. Additionally, a free FMI compliance checker is available and FMI models from different tools are made available on the web to simplify testing.

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“…[1,5] "Green Building" -Modelling renewable building energy systems and electric mobility … The granularity and complexity ( fig. 1) of each element is comparable to the approach used in the automotive industry (e.g.…”

Section: Modelica Green Building Librarymodeling Paradigmsmentioning

confidence: 99%

"Green Building" - Modelling renewable building energy systems and electric mobility concepts using Modelica

Unger¹,

Schwan

Mikoleit³

et al. 2012

Linköping Electronic Conference Proceedings

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For most people, a comfortable living and mobility are basic needs. With the rising individual demand for energy as well as the diminishing fossil energy resources, new optimized concepts for energy supply and usage are required. To address these challenges, renewable energy sources, decentralized storage, and electric mobility concepts are matters of rapidly growing importance.Future building energy systems have to successfully integrate user demands, local renewable energy, storage systems and charging infrastructure, a task requiring extensive scrutinizing.Typical questions to the engineer are to compare different system layouts with respect to sustainability, cost, and robustness, or to identify the right levers in an energy system to optimize components and control algorithms. This paper describes an approach to solve such questions using simulations with the non-causal language Modelica. Modeling paradigms and examples are shown. Special emphasize is given to the "Green Building" library and its components, bringing major building energy systems and electric vehicles to the same platform.

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Simulation-based development of automotive control software with Modelica

Cited by 17 publications

References 1 publication

Fault Localization Method by Partitioning Memory Using Memory Map and the Stack for Automotive ECU Software Testing

Fault Localization Method by Partitioning Memory Using Memory Map and the Stack for Automotive ECU Software Testing

Functional Mockup Interface 2.0: The Standard for Tool independent Exchange of Simulation Models

"Green Building" - Modelling renewable building energy systems and electric mobility concepts using Modelica

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