How does software define smart cars?

liu, tempo Date: 2021-09-13 09:57:21
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Software is reshaping the ecological value of the automobile industry and changing the profit model of automobile enterprises. The century old traditional automobile industry is blowing a wave of innovation, and the automobile industry with a long history is actively turning to software innovation. In terms of software code volume, the code volume of common smartphone operating system Android is 13 million lines, that of PC operating system Windows Vista is 50 million lines, and that of high-end vehicle software has reached 100 million lines, with exponential growth. It is predicted that from 2021 to 2025, the average annual compound growth rate of code volume in vehicles will reach 21%.


The traditional automobile industry is setting off an upsurge of transformation and upgrading around the “software defined vehicles (SDV)”. It is estimated that the scale of automotive software market will increase from 1.85 trillion yuan in 2020 to 3.44 trillion yuan in 2030, with a compound annual growth rate of 7%. The proportion of Automotive Software in the vehicle value is expected to reach 65% by 2030 and become an important profit point in the future automotive industry.


With the sweeping of the “new four modernizations”, the automotive industry in the past century is changing rapidly, the content structure of global automotive software and hardware products is undergoing significant changes, and the era of software defining Automotive has come.


“Both soft and hard” to consolidate the hard strength of automobile

Because the distributed EE architecture adopted by the traditional automobile has the disadvantages of insufficient computing power, insufficient communication bandwidth and inconvenient software upgrading, it can not meet the needs of automobile development at this stage, nor can it realize the new function of “software definition”. The EE architecture needs to be upgraded urgently. A new generation of centralized EE architecture came into being and became an important hardware foundation of “software defined automobile”.


For example, Tesla Model 3 uses a powerful central controller to uniformly manage different domain processors and ECUs, and divides the electronic and electrical architecture of the whole vehicle into three parts: CCM (central computing module), BCM LH (left body control module) and BCM Rh (right body control module). CCM further integrates Adas (driving assistance system) and IVI (information and entertainment system) Two domains, external connection and in vehicle communication system domain functions.


This not only greatly reduces the number of ECUs on the whole vehicle, but also realizes the effective utilization of computing power in the domain, greatly improves the core computing performance and greatly reduces the difficulty of complex function development. While consolidating the hardware foundation, it is also essential to upgrade the software foundation. In order to realize software defined vehicle, the software architecture of intelligent vehicle needs to be transformed and upgraded to SOA (Service-Oriented Architecture). SOA architecture is the software foundation to realize software defined automobile.


The underlying software under SOA Software Architecture has three characteristics: interface standardization, mutual independence and loose coupling. Each service is independent and unique, and belongs to the basic software in the automotive software architecture. Therefore, if you want to upgrade or add a function, you only need to call it through the standardized interface, and the moped enterprises can build their own software hardware strength.


Predictably, the automobile is highly intelligent, greatly improving the position of software in the automobile value chain. With the dual upgrading of hardware foundation and software foundation, “software defines automobile” has become the strategic consensus of enterprises at the head of the industrial chain.


Automotive Software


Automobile enters the “computing age”

The intelligent level of intelligent driving vehicles depends on the strength of algorithms, so intelligent driving vehicles have a strong demand for computing power. At present, the automotive industry has regarded the peak computing power as the main index to measure AI chips, and set off an arms race in automotive computing power. Under the trend of “software defined vehicle”, chip, operating system, algorithm and data together form the computing ecological closed loop of intelligent driving vehicle, in which chip is the core of the ecological development of intelligent driving vehicle.


The pioneer of automotive electronic and electrical architecture reform represented by Tesla took the lead in adopting the centralized architecture, that is, a computer controls the whole vehicle, and the domain controller gradually integrates the early sensor, data fusion, path planning, decision-making and other computing processor functions. Therefore, the demand for the computing power of the domain controller chip has increased significantly.


With the trend of mass production of intelligent driving vehicles, computing power, power consumption and ecology have become the core competitiveness of chip manufacturers to seize the market. It is understood that there are two major development trends of automatic driving SOC chip products: first, not only pay attention to computing power, but also pursue high power consumption ratio; Second, high-end autopilot chips are advanced to advanced processes.


At present, the global automotive MCU chip market has been monopolized by automotive chip giants such as NXP and Texas Instruments. With the acceleration of the automotive industry into intelligent transformation, a business war with high-level automatic driving SOC chip as the core has begun. Consumer electronics giants such as Intel, NVIDIA, Qualcomm and Huawei have ended one after another. China’s horizon, black sesame intelligent technology and other start-ups have also come to take a share.


With the development of intelligent driving vehicles and the landing of business scenarios, the gap between automatic driving companies in terms of algorithms will gradually narrow, and data will become an important factor that really affects the level of automatic driving technology. In the future, big data will help automatic driving technology to a new level and push the automobile industry into the computing era.


In the process of promoting the development of automatic driving technology, there is no lack of leaders of local enterprises. For example, SAIC intelligent control empowers traditional cars in a low-cost and efficient way, creates a “brain of automatic driving” for them, and promotes the transformation and upgrading of traditional car enterprises; Zhixing is committed to creating L4 & L3 overall solutions for multiple general scenarios. At present, it has realized the commercialization of multiple scenarios, and has become the first company with driverless mass production capacity in China.


How to reconstruct automobile value ecology by software

With the development of electric and intelligent vehicles, the cost structure of vehicles is changing. In addition to the battery of the core cost of the whole vehicle, the cost of automotive electronics is also rising. According to the cost of an intelligent new energy vehicle, the cost of intelligent network connection accounts for 13.7%. As the connection between car enterprises and C-end consumers becomes closer and closer, the operation cost of car enterprises is virtually increased; In addition, the automobile industry is accelerating innovation, and there is an urgent demand for compound talents. Automobile enterprises have to bear too high talent costs for innovation and development. Under the influence of comprehensive factors, the profitability of the automotive industry is continuing to decline.


Traditional automobile enterprises urgently need to develop the “second growth curve” of profitability.At present, the automobile industry is in a period of great change, emerging concepts such as electrification, intelligence, networking and sharing have emerged, the profit model has changed, and it is changing from single vehicle sales revenue to mobile travel integrated service revenue. At present, traditional automobile enterprises and Tier1 have started intelligent transformation one after another, and the real embodiment of the differentiated competitiveness of automobile enterprises in the future is at the software level.


With the improvement of automobile intelligent level and the substantial penetration of software technology, it will form the basis of secondary charging service for automobile enterprises. At present, the global automotive software and hardware product structure is undergoing significant changes. The proportion of software drivers has increased from 5% in 2010 to 16% in 2016. It is expected that the proportion of software drivers will reach 35% in 2030, and the value status of software will be greatly improved, laying a solid foundation for software profitability.


Tesla took the lead in implementing the mode of “hardware as traffic entrance and software as charging service”. At present, Tesla can realize rapid software iterative upgrading, and then establish a software payment model to further open profit space. The catfish effect brought by Tesla has prompted traditional vehicle manufacturers to accelerate the transformation and layout of the field of on-board software, and accelerate the arrival of the era of software defined automobile.


Software is reshaping the ecological value of the automobile industry and changing the profit model of automobile enterprises. The profits of hardware and manufacturing will maintain a reasonable and low level. In the future, software profits and service revenue will become the valuation anchor of the new era. The profit model of automobile enterprises may focus on software and services. When “software defined car” becomes the mainstream consciousness of the industry, the car is no longer a cold machine, but a “third space” with temperature. Software defined automobile not only brings changes in automobile functions, but also lays a solid foundation for the innovation of automobile business model and creates emerging market opportunities for the upstream and downstream of the industrial chain.

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