Agilent Measurement Journal - Issue 5 - 2008 - (Page 59)

node A node B node C node D node E node F Channel a Channel b Static segment dynamic segment SWIN NIT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 0 0 1 Slot a A C D A E F 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 0 0 1 Slot b A B C B A C t Figure 2. FlexRay segment conﬁguration consists of the static segment with the ﬁxed time trigger method and the dynamic segment with the ﬂexible time trigger method. Speciﬁc measurement tools are required to create quality metrics for FlexRay’s physical and protocol layers. Measurement tools are currently available to help create the protocol layer quality metric; however, this is not yet the case for the physical layer. No complete test solution is currently available to address this need. Instead, it is incumbent on the measurement industry to provide — as soon as possible — a measurement device that can fulﬁll this need. This is the only way to help FlexRay realize its promise of reliability, real-time capability and robustness for the physical layer. speciﬁcation only deﬁnes a mask for this type of connection topology. Second, due to the internal architecture of many oscilloscopes, a period of dead time occurs after each trigger and before the next trigger event can be captured. During this dead time, the scope is essentially inactive, preventing a continuous measurement and making it virtually impossible to cover 100 percent of all bit transitions — a prerequisite for safety-critical applications such as X-by-wire systems. • Use of a bit error rate tester (BERT) to validate the quality of a network and its physical connections. For a number of reasons, this method is not viable for the FlexRay network. To begin with, in order to calculate the bit error rate, the BERT must know what sort of data is coming so that it can compare the incoming data stream to the expected data. In a dynamic, non-deterministic system such as a car, this is simply not possible. Additionally, in a FlexRay network, each ECU has its own clock, which is used for data transmissions. Because BERT measurements require synchronization with a common unique clock, this default, bit error rates show no errors in lab and test usage. Robustness, while not needed in test versions, is required in the ﬁnal product. In order to make a valid and statistically sound statement at a 10-12 bit error rate, test times simply become impractical. Assessing the physical layer Creating a quality metric for FlexRay’s physical layer requires the use of an appropriate measurement approach and solution. There are several approaches that are not well-suited to this task. They include: • The classical method of using an oscilloscope, capable of producing an eye diagram, to measure electrical signal quality. This approach is not suitable for FlexRay networks for two reasons. First, each individual protocol speciﬁcation deﬁnes clear masks for eye shapes that indicate compliance. In the case of the FlexRay protocol, this approach is viable only when using a point-to-point connection topology (Figure 3). That’s because the FlexRay Agilent Measurement Journal 59

Table of Contents Feed for the Digital Edition of Agilent Measurement Journal - Issue 5 - 2008

Agilent Measurement Journal Issue 5 Finding a New Path when Assumptions Break Down Contents Testing MIPI D-PHY Protocols Oscilloscope Firmware Update DNA Replication Joining the LTE/SAE Trial Initiative Testing Proteins Praise for DC Power Analyzer Scripting Features for AMDS Testing Hybrid PCBA Systems Improving the Gene Expression System Workflow Turning a “Good Enough” Test Strategy into One That’s Reliable, Repeatable and Traceable Understanding the Effects of Limited-Bandwidth Channels on Digital Data Signals Introducing the 3GPP LTE Downlink Validating the 26 Validating the Physical and Protocol Layers in DDR Memory Interfaces Understanding Total Jitter Measurements of Low Probabilities Using Behavioral-Model Simulation to Accurately Predict First-Order PLL Performance Creating Synchronous High-Frequency Sampling across Multiple Digitizers Overcoming the Challenges of Testing FlexRay Networks Understanding Operating Life and Repeatability of Electromechanical Switches and their Effect on Total Cost of Ownership Implementing Micro and Nano LC/MS Techniques for High Sensitivity Lipidomics Analysis

Agilent Measurement Journal - Issue 5 - 2008

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