Software-defined vehicles

A software-defined vehicle is a cutting-edge automotive concept that redefines traditional vehicles by prioritizing software control and adaptability. It leverages advanced computing systems to manage and customize crucial vehicle functions such as powertrain, suspension and safety features. By centralizing control through in-vehicle and off-vehicle software, manufacturers gain unprecedented flexibility to update, optimize and personalize vehicle performance remotely, enhancing user experience and longevity. This approach allows for seamless integration of emerging technologies like artificial intelligence, connectivity and autonomous capabilities.

Automotive manufacturers are shifting their focus to software-defined vehicles (SDV) due to the potential to differentiate their offerings, improve operational efficiency through remote diagnostics and updates, and future-proof their vehicles against rapid technological advancements. Developing SDVs successfully requires upfront architectural decisions that consider software and the resulting implications on hardware as well as the various interfaces to sensors and actuators. Additionally, manufacturers must incorporate long-term scalability to enable remote maintenance and upgrades.

Automotive Open System Architecture AUTOSAR is a worldwide development partnership of automotive-interested parties. The primary goal of the AUTOSAR development partnership is to provide a leading solution for automotive software platforms by standardizing basic system functions and functional interfaces. The framework enables the efficient development of embedded application software that supports tasks surrounding essential automotive functions in vehicle system development. Capital ® Embedded AR Classic ™, part of the Siemens Xcelerator portfolio, is an example of software for implementing the AUTOSAR standard. It is a complete offering with tools and software to meet all electronic control unit (ECU) platform needs, from ECU extract updates to software platform configuration.

Software integration testing in the automotive industry focuses on verifying that different software components work together as intended when integrated into the vehicle's overall system. It ensures seamless communication and compatibility between various subsystems. The most efficient software integration testing includes simulation tools and virtual environments to simulate real-world driving scenarios and test the behavior of the integrated software under different conditions. This virtualization allows for comprehensive testing without the need for physical prototypes. Once the software integration is complete, vehicles must undergo extensive field testing in real-world conditions to validate performance, reliability, and user experience. Data collected during field tests enables a closed-loop feedback system to help identify any issues or areas for improvement. Siemens offers the following proven testing solutions from the Capital portfolio, curated for the automotive industry:

• Capital Embedded Integrator AR Classic is a powerful solution for the complete configuration of the AUTOSAR middleware components.
• Capital Embedded Virtualizer AR Classic], the ECU is simulated so software tests are controllable with unique, non-intrusive trace for deep analysis.
• Capital Embedded AR Classic software is our implementation of the AUTOSAR Classic platform.
• Use Capital Network Designer to design, verify, and validate software communications over standard protocols, such as CAN, CAN FD, LIN, FlexRay, and Ethernet (SOME/IP, TCP, UDP, DoIP, DDS).

Verification and validation are crucial in engineering software-defined vehicles to ensure that the integrated software functions correctly, meets performance standards, and complies with safety regulations. Verification confirms that the software is built according to specifications and design requirements, while validation ensures that it meets user needs and operates reliably in real-world conditions. Insufficient or delayed verification and validation can lead to software errors, safety hazards, and compliance issues which may result in recalls and damage to brand reputation.

Siemens assists with verification and validation by combining realistic system models in co-simulation scenarios to validate early software architecture assumptions in the context of electrical and network architectures. By enabling continuous evaluations that can be performed with stakeholders across multiple engineering domains, tradeoffs like weight, cost and power consumption can be balanced before moving on to domain-specific engineering activities. Individual domains can then validate functional interfaces, generate options, verify requirements, ensure cybersecurity and evaluate hardware and software decisions with simulation in a virtual environment.

As software is implemented, Siemens solutions can generate verified and validated ECU extracts to facilitate application software integration with the base software for the configured ECU. This allows engineers to test the execution of application software in real time with a virtualized ECU and actual network communication data. As a result, engineers can develop complex software faster and deliver high-quality products to their customers.

A semi-luxury or luxury vehicle on the road today is estimated to have over 100 million lines of code executing at any given time. Ensuring a flawless driving experience in this complex environment requires hundreds of computing units to work flawlessly in real-time. In recent years, manufacturers have increasingly focused on optimizing the software needed to execute this hardware and leveraging software alongside technologies like artificial intelligence (AI) to differentiate their products. This approach to automotive development has been labeled the software-defined vehicle, where software is rapidly becoming the key to how a vehicle gets engineered, produced, serviced and acts as the edge to collect consumer intelligence data. The main differences between a software-defined vehicle and a traditional vehicle are as follows:

• Control: In a software-defined vehicle, control is primarily managed through software systems, whereas in traditional cars, control is mainly mechanical, relying on physical components like levers, cables and hydraulics.
• Adaptability: Software-defined vehicles can easily adapt their functionalities remotely through software updates, offering flexibility and customization options to users. Traditional vehicles lack this adaptability and typically require physical modifications for updates.
• Integration of emerging technologies: Software-defined vehicles seamlessly integrate emerging technologies like artificial intelligence (AI), connectivity and autonomous capabilities. Traditional cars may not have the infrastructure or compatibility to incorporate these advanced features without significant retrofitting.
• Longevity and maintenance: Due to their software-driven nature, software-defined vehicles can potentially have longer lifespans and require less frequent maintenance compared to traditional vehicles. They allow for remote diagnostics and updates, enabling manufacturers to address issues quickly and efficiently, whereas traditional cars may require more hands-on maintenance and repairs.