Read any automotive-related article and I’m sure it discusses autonomous cars and Advanced Driver Assistance Systems (ADAS) – the benefits, the challenges and what the future may hold. More and more auto makers are moving towards autonomous developing vehicles, but many of the systems that will eventually be integrated into these vehicles to make them fully autonomous are being developed today. In fact, you probably have some of them in the car you are driving now — Collision Mitigation Braking, Lane Departure Warning, Blind Spot Warning, and Lane Keeping Assistance to name a few. These ADAS applications present a new set of challenges and require a multi-disciplinary development approach. You can read more about these development areas in a blog written by my colleague, Sandeep Sovani.
Spring is just around the corner in many parts of the world and so is Embedded World 2017, which takes place on March 14-16 in Nuremberg, Germany. Embedded World brings together over 30,000 professionals focusing on embedded systems and software tools, and I’m pleased to let you know that ANSYS will be attending again this year in booth 4-303.
We talk about product complexity and how the product development process is changing quite a bit here on the blog and the same holds true for the embedded sector and embedded systems and software tools. More and more products are controlled by embedded software and this software must behave as planned. This not an easy task.
Today’s automotive systems are more complex, smarter and more autonomous than ever before, featuring functionality that no one could have imagined 10 years ago. Advanced sensors and electronics control everything from a vehicle’s speed and position to its entertainment and communications technologies. Radar, cameras and other sophisticated electronics are increasingly being incorporated into consumer vehicles.
In fact, today, more than 60 percent of a car’s cost comes from its advanced electronics and software systems. Since many of the functions guided by electronic systems are mission-critical, it’s essential that all automotive systems work together with complete reliability. The tens of millions of lines of software code that control these systems must be flawless. Continue reading
A number of new and exciting workflow enhancements were included in ANSYS SCADE 17.2 for those who are validating and testing embedded software. In this blog, I’ll cover the top 3 enhancements.
Virtual System Testing Using Simplorer Entry
In ANSYS 17.2, all SCADE Suite users can immediately simulate and analyze virtual system prototypes thanks to the bundling of Simplorer Entry.
One of the main objectives of embedded software users is to perform closed-loop testing to tune the software application — as early as possible. As a best practice, embedding the application within a virtual environment is a great way to reduce testing costs. It can be performed first with simplified model of the environment using Modelica language then moved to high-fidelity models. Continue reading
Developing an Internet of Things (IoT) enabled product is a complicated task, whether it’s an autonomous vehicle, a vehicle user interface like a car infotainment system, or a connected factory. IoT-enabled products contain hundreds, if not millions, of lines of embedded software code. And many of these products — and the systems and software that control them — are mission- or safety-critical. Therefore, developers must have confidence that the software code controlling these devices is 100% accurate and responds in the intended manner. Continue reading
The Internet of Things and the abundance of smart applications have significantly increased the need for the safety critical embedded software that controls these devices. You’ve probably heard some of the following stats. Nearly 400,000 software and system engineers work in the oil and gas industry. In the energy and nuclear sectors, software-based instrumentation and controls have become state of the art. The aerospace industry has witnessed a 500 percent increase in source lines of code over the past decade. And, there are 10 million software lines of code in modern vehicles! Continue reading
The tragic derailing of an Amtrak train near Philadelphia points out just one of the challenges facing the modern railroad industry — safety. The industry also must contend with rising energy costs, fast growth of capacity requirements in emerging markets, increasing certification costs and interoperability requirements. Continue reading
The model-based systems engineering journey is evolutionary, not revolutionary. Deployment often starts with a single project or disciplinary area and becomes more sustainable as its business value is demonstrated. We’ve been studying MBSE deployments and the business value it delivers for some time now. Below I’ve shared some key success factors we’ve observed with deploying a sustainable MBSE initiatives, but first I’d like to share and event coming up that I think you may enjoy. Continue reading
Today’s blog post is a continuation of a series on Systems Engineering for Smart Products. Remember the old Xerox commercial featuring a monk tasked with making 500 copies of a multi-page, handwritten document? Well, fast forward to 2014 and replace the monk with a systems engineer verifying hundreds of requirements against a textual-based description of a product, and you have a typical scene playing out across many engineering enterprises. Continue reading
“A picture is worth a thousand words.” Pictures, or model-based designs, as engineers refer to them, provide a natural means of communication. With the newest release of ANSYS SCADE System 15.2, systems engineers can use models and interface control documents (ICDs), rather than text files and long lists of data, to create and manage their systems designs.
However, when precision and complexity come forth, “data dictionaries” enter the game. A dictionary is a way to manage information in an exhaustive way but without the model, it’s not easy to get an overview of your system. The issue you’re then faced with is the consistency between the model and the dictionaries — if inconsistent, the situation is worse than without the model. Continue reading