The challenges facing the automotive industry today are similar to those experienced by the telecommunications industry more than a decade ago. New technologies such as hybrid electric vehicles and fuel cell vehicles have also contributed to the growing activity of R&D activities, as we have seen in the evolution of mobile phones into multimedia devices. Similarly, the telecommunications industry is facing power and chip size limitations, and automotive designers are working hard to apply more technology to devices that used to be mechanical.
Electronic, electrical, mechanical, hardware and software components and the networks that connect them are driving the development of automotive design. The proportion of in-vehicle electronic devices is currently 40% and is rising. At the same time, the number of electronic control units is increasing and distributed throughout the system to control the sophistication and complexity of new applications. The electronic control unit can contain hundreds of software components, making the system more multiplexed and improving communication requirements.
Not only does the general system design expand as a whole, it can meet ever-increasing functional and performance requirements, and these designs must seamlessly integrate analog and digital hardware and control software. Successfully integrating and coordinating system components and completing verification has proven to be time consuming, capital and design resources. At the same time, this puts higher requirements on shortening the development cycle.
New processes and development tools are needed to meet new requirements. In particular, the development and intelligent use of computer models in these complex systems (previously considered a luxury) is becoming the key to the success of the entire development process.
Why is it so difficult to design a complex system? Let's take a look at where the boundaries of the design process are.
The components provided by the extensive, multi-level supply chain are assembled into automotive systems. The process of loading system components into subsystems and re-injecting subsystems into the system spans many industry boundaries. These boundaries create barriers to intellectual property that prevent or prevent the spread of design information at the top and bottom of the supply chain. System designers in the OEM field can benefit from comprehensive subsystem and component performance information. Disclosure of relevant information may lead competitors to use reverse engineering techniques to improve their designs, so suppliers are very cautious about this. Similarly, once original equipment manufacturers publish specifications, their suppliers can get detailed information about the entire system environment, but original equipment manufacturers are also worried that their innovation in system design may be exploited by competitors in the supply chain. . The need to disseminate critical performance and content information, as well as to protect critical design intellectual property, creates a major gap in the automotive system design process.
Another line of demarcation is the distribution of design process information across the design centers around the world. We need to manage system and component design across time zones and languages, and we must always provide comprehensive specifications and performance data to those in need. In addition, the sender of the data must have a clear and clear understanding of the data, whether or not it is in their native language.
Technical specialization is the third line. In various subsystems, even in many components, multiple technologies must be combined into one. To this end, it is necessary to integrate technologies such as electronics, magnetism, mechanics, and hydraulics, and to bridge the differences in design processes and terminology across different engineering disciplines.
Then there is the additional challenge brought by the increasing content and relative importance of in-vehicle software. Many subsystems not only need to integrate hardware into the vehicle structure, but also integrate software into the vehicle network/processing infrastructure. The issue of hardware/software co-verification highlights a new dimension in the boundaries of technical specialization.
There are common bottlenecks in the system integration phase. In a distributed system, data comes from different internal resources. For example, electronic control units come from different companies, different electronic control units have different algorithms, and these must be coordinated. The essence of distributed systems is that they require a lot of coordination.
To make matters worse, the currently accepted design and analysis methods do not provide insight into design work that is uncontrolled or unobservable in the lab. Integrating different subsystems and components into a unified system is a risky, troublesome, and unpredictable process. At this time, if there is an unexpected problem in the project, the subsystems and components need to be redesigned, and even the system requirements should be further improved, which often delays a lot of time.
One of the key challenges in integrating systems is the network infrastructure with communication capabilities. Despite the many optional network technologies, these techniques are often used to emphasize innovative tasks that pursue maximum capabilities and performance. Designing the network in a modeled form and analyzing its characteristics in extreme operating environments can help reveal the problem – and optimize the bandwidth and margin of safety so that costly rework and significant production can be avoided early in the design process. Delay.
Model-driven design and analysis, including system modeling and simulation, can solve these numerous problems. In the field of systems engineering, analytical methods often come in many forms. Many companies currently use Excel to deal with complex issues, but spreadsheets have so far been of limited use to designers. True system modeling provides an interactive environment where designers can verify a small part of the entire puzzle, and any minor changes in the entire puzzle can affect the end result.
Simulation is often thought of as a tool that helps automate the design of a specific aspect of the system, enabling continuous verification of new designs from concept to implementation. Using a model-based design approach, system designers can take advantage of models based on transformation capabilities, RTL, calculation rules, and even specifications. Component designers can validate design implementations (such as circuits, mechanisms, logic, or cores) in an original advanced system model environment using a hybrid level verification approach in the design process. System and component designers can work together to validate the complete system in a specific implementation process with detailed verification of the final design. As design work progresses, continuous verification of concepts and components can increase opportunities for early detection and resolution, saving time and money.
Another benefit of model-based design is the support for stability design (such as Six Sigma design). A separate component model can characterize manufacturing and environmental changes, so the integrated system model will reflect overall variability. Accuracy stacking can be evaluated, reasonable system boundaries can be established, and end effects that reduce warranty costs can be achieved.
The most important benefit is the value of simulation as a learning platform, although the benefits are subtle and less clear, but they can be verified. It is difficult to price knowledge, intuition, and insights gained from researching system design, changing parameter values, trying various stimulus and load states, and testing other configurations and variables. Exploring and learning is the foundation of all innovation.
Modeling overall system changes can also help prevent designers from optimizing components while ignoring the overall system. For example, it may be possible to reduce the cost of one component by lowering the accuracy requirements, but its chain reaction may eventually lead to higher adjustment costs for another component, at a higher cost to offset changes to the overall system. As long as you understand this impact, you can be dismissed before such changes can't be cancelled.
Simulation can do things that physical hardware can't do, and see the results that physical hardware can't see. For example, a designer can simulate a system that is operating at excessive voltage or temperature values ​​to view current, flux, or other state variables within a device. Another example is the ability to emulate an embedded controller running in its hardware peripherals (such as A/D converters, D/A converters, timers, etc.). This is similar to the in-circuit simulator used in the real world, except that in the real world, users can actually stop the timer at the breakpoint, not just execute the code.
The IEEE 1076.1 standard for VHDL-AMS language is combined with a multi-language simulator to fill the gap in the design process of automotive systems. Using modeling and simulation techniques, automotive system designers can reduce issues related to intellectual property protection, enhance communication between design stakeholders around the world, and integrate technical content. Model compatibility can be maintained at all stages of the design process from initial concept exploration to final hardware software verification.
With VHDL-AMS, hardware modeling is ideal for network signal integrity analysis. This includes modeling of the analog, digital, and mixed-signal aspects of the transceiver, as well as modeling of the operation of twisted-pair transmission lines, connectors, and other components of the network physical layer. The model is provided by the component supplier and is usually available at the beginning of the purchase. The original model was based on expected performance, but as the module design evolved, the model was continuously updated and refined, and in the end even included precise manufacturing precision.
Since the technology used is based on a behavioral model and therefore does not contain data on the details of the internal equipment structure design, the supplier is also willing to share it with other members of the supply chain. As a result, designers can use models to assemble or disperse complete system test platforms, and all vendors can explore and validate innovative methods for improving quality. It also provides OEMs with an effective platform to communicate overall system requirements and individual component specifications.
Models written in the VHDL-AMS language can run on any emulator that supports the standard, providing a choice of simulation products that leverage price, performance and feature set advantages through competition among tool vendors, all of which have advantages Conducive to the development of the automotive industry.
While specialized or proprietary modeling and simulation techniques are still useful in separate design activities, successful system design is inseparable from the desire to work together extensively, use new technologies, and accept short-term transition costs.
Virtual system-level integration and validation based on legacy executable specifications is primarily a walkthrough providing a rich tool integration environment. System integration can begin before the physical hardware is obtained, and a system model can be built by combining various technologies. This may include mechanical, magnetic, hydraulic, and thermal effects, or any other technique described by algebraic or differential equations. Although obviously of high value, these advantages are only apparent in the design of automotive systems when many designers working in systems and components and in all engineering fields begin to use system modeling techniques.
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