Software-defined automotive vECU virtual controller integrated development and testing

summary

Over the past two decades, the demand and application of automotive software has grown dramatically, and with it the complexity, existing technologies and frameworks are not adequate to handle this complexity. It is now clear that automotive manufacturers (OEMs) must rethink the way they produce vehicles and the life cycle of the vehicle itself. By focusing on software, OEMs can enable many new application use cases throughout the vehicle life cycle and open up a new world of opportunities.

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Software-defined cars and virtualization technology

1.1 The concept of software-defined cars

In the era of mobile travel, cars have gradually transformed from purely mechanically driven hardware to software-driven electronic products. Today, the hardware configurations of products from different car manufacturers have gradually converged. With limited room for cost and function improvement, the reconstruction of the traditional automotive value chain is imperative. The core element for car manufacturers to create differentiation has shifted to automotive software that was originally deeply coupled with hardware. With the continuous success of automotive software in the fields of new energy and intelligence, entering the era of "Software Defined Vehicles (SDV)" has become an industry consensus.

"Software-defined car" means that software will be deeply involved in the definition, development, verification, sales, and service of the car, and will constantly change and optimize each process. It is the result of the continuous transformation of the car from a hardware-based product to a software-centric electronic device.

On the surface, "software-defined cars" means that the number and value of in-car software (including electronic hardware) exceeds that of mechanical hardware. Behind this, it reflects more the gradual transformation of cars from highly mechatronic mechanical terminals to intelligent, scalable, and sustainable iterative mobile electronic terminals. To achieve this goal, the whole vehicle is pre-embedded with advanced performance hardware before the standard operating procedures, and gradually unlocks and releases functions and value during the life cycle through OTA. In this context, the core capabilities of OEMs will shift from mechanical hardware to electronic hardware and software; the industry value chain will also shift from one-time hardware sales to continuous software and service premiums.

1.2 Development Trends of Automotive Software

The "new four modernizations" of automobiles are inseparable from software and algorithms. With the in-depth development of the new four modernizations, automobiles are accelerating their transformation from mechanical equipment to highly digitalized and information-based intelligent terminals.

First, the proportion of software and automotive electronics in the R&D cost of the whole vehicle is gradually increasing. The value of in-vehicle software and electronic hardware is expected to exceed that of hardware and become the core of the value of the whole vehicle. According to estimates, the proportion of software costs in the whole vehicle BOM (Bill of Materials) is expected to increase from less than 10% at present to 50% by 2030. It should be pointed out that the software here includes not only application development, but also AI algorithms, operating systems, and electronic hardware such as controllers and chips with a high degree of software and hardware integration.

Secondly, the performance and functional changes brought about by software and software iterations will determine the differentiation of future cars. Software updates and maintenance are the most economical, convenient and fastest way for OEMs to provide differentiated experiences and improve customer satisfaction in the future. The premise is that hardware provides redundancy and software implements iteration.

Finally, companies in the industry chain, including OEMs and parts companies, will strengthen their software capabilities and start internal changes in product development models, organizational structures, personnel composition, and operating systems around "software-defined cars." In addition, emerging software companies will leverage software and hardware collaboration capabilities to accommodate the needs of multiple parties in the industry chain, and become new Tier-1 companies in the automotive industry chain.

1.3 Dilemma faced by automobile R&D

First, the distributed electrical and electronic architecture cannot meet the future demand for higher vehicle computing power. Another driving factor for the EEA architecture upgrade comes from the demand for higher communication efficiency and greater bandwidth capacity. Cost control black hole: As the number of ECUs and sensors in the car increases, the cost and difficulty of wiring harnesses for the entire vehicle also increase significantly.

In addition, the modularization and platformization of automotive software are low, which leads to the inability to centrally schedule software resources and poor collaboration. The ECUs of OEMs usually come from different parts suppliers. In fact, many underlying software on the controllers are highly repetitive. These codes mainly guarantee the normal operation of the controllers, such as the sending and receiving of CAN bus signals, the scheduling of task processes, the reading and writing of Flash data, etc. However, due to the different software programming languages ​​and interface standards of each supplier, and the high dependence of software on hardware, these underlying codes cannot be copied and transplanted, resulting in a large amount of duplication in ECU software development and inefficient resource utilization.

Secondly, the hardware and software are highly nested, and the OEM cannot perform large-scale, in-depth updates and upgrades or customized development work. Distributed software architecture is a signal-oriented architecture, where information is transmitted between controllers through signals, but the entire system is closed and static, and is defined in the compilation stage. Therefore, when the OEM wants to modify or add a function definition of a controller, and the instruction must also call a function on another controller, all required controllers have to be upgraded, which greatly prolongs the development cycle and increases development costs.

1.4 Changes in R&D Model

Based on the above changes in technical architecture, in the context of software-defined cars, automotive R&D will shift from traditional waterfall development to agile development model.

Agile software development: includes demand discovery and solution improvement. This model collaborates with users through self-organized and cross-functional teams to develop adaptive plans, conduct incremental development, early delivery, and continuous improvement, and flexibly respond to changes in demand, capabilities, and understanding of problems that need to be solved. This is an iterative, step-by-step development method centered on the evolution of user needs. Engineers first make the software prototype that users are most concerned about for delivery, and quickly modify it to make up for the deficiencies in the requirements based on the problems reported by users in actual scenarios. The above process is iterated continuously until users are satisfied.

DevOps is a general term for a set of processes, methods, and systems that integrates cultural concepts, practices, and tools, and emphasizes communication and cooperation between development (Dev), operations (Ops), and quality (QA) departments.

Compared with the traditional software development model, DevOps breaks down the barriers between development and operation and maintenance. By automating the processes of "software delivery" and "architecture change", it makes software building, testing and release faster, more frequent and more reliable, thereby helping teams develop and improve products faster, serve customers and participate in market competition more efficiently.

1.5 The value of virtualization

Automotive software development will follow the development laws of the IT industry and introduce middleware technology and virtualization technology to achieve software modularization, hardware abstraction and standardization, thereby further unlocking the coupling relationship between software and hardware and meeting the flexible and scalable needs of electronic and electrical architecture.

To meet the challenges of process transformation, the development team can consider decoupling the hardware and software, developing the hardware and software parts according to independent timelines, and not needing to re-verify the entire vehicle after making software changes. The pure software development and verification process transitions from prototype or hardware-in-the-loop testing to software-in-the-loop (SiL) testing and verification. This decoupling of hardware and software also caters to the current trend of integrating ECU functions into central computing units or domain controllers, and plays a role in the process of all-in-one controller integration. Hardware and software modules can run on different hardware platforms and be updated throughout the vehicle's life cycle.

So what are the application scenarios of software-in-the-loop (SiL)? Its application scenarios are usually agile development and rapid iteration under rapidly changing functional requirements. It is required to verify the software as early as possible and find and correct important errors in the code, especially those related to safety. Automatic continuous verification in the case of high-frequency OTA cloud software upgrades. In the above scenarios, software-in-the-loop (SIL) testing can quickly verify the functional code of the controller without hardware.

One of the most critical cores of Software-in-the-Loop (SiL) is virtualization: that is, by converting the real controller into a virtual controller, deploying it to the integrated environment and joint simulation platform on the PC, connecting it to the CI/CT/CD automated pipeline, and conducting large-scale testing on the cloud, a complete DevOps SiL platform can be built.