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Semiconductors for Autonomous and Electric Vehicles 2023-2033


自律走行車・電気自動車向け半導体 2023-2033年

この調査レポートは、電動化や自律走行車(AV)といった自動車業界のメガトレンドが、半導体業界に新たな成長とチャンスをもたらしていることについて詳細に調査・分析しています。   主な掲載... もっと見る

 

 

出版社 出版年月 電子版価格 ページ数 言語
IDTechEx
アイディーテックエックス
2023年3月23日 US$7,000
電子ファイル(1-5ユーザライセンス)
ライセンス・価格情報
注文方法はこちら
358 英語

※ 調査会社の事情により、予告なしに価格が変更になる場合がございます。
最新の価格はデータリソースまでご確認ください。


 

Summary

この調査レポートは、電動化や自律走行車(AV)といった自動車業界のメガトレンドが、半導体業界に新たな成長とチャンスをもたらしていることについて詳細に調査・分析しています。
 
主な掲載内容(目次より抜粋)
  • 半導体製造、サプライチェーン
  • アドアスセンサー、自律走行車用センサー、車載用ハイパフォーマンスコンピューティング用半導体
  • 電動化用半導体:車載充電器、バッテリーマネジメントシステム、インバーター
  • 車両通信とインフォテインメント: 新たな機能と実現するハードウェア
  • 欧米CHIPS法
  • 予測
  • 会社概要
 
Report Summary
The "Semiconductors for Autonomous and Electric Vehicles 2023-2033" report provides a deep dive into how megatrends in the automotive industry, such as electrification and autonomous vehicle (AV) are bringing new growth and opportunity to the semiconductor industry. These trends require new componentry on vehicles, such as LiDAR in automation, and with them new semiconductors, such as indium phosphate laser emitters. Eighteen components across the areas of advanced driver assistance systems, automated driving, electrification, communications & infotainment, and general MCU architectures are analysed for semiconductor content and trends which will impact semiconductor technologies used.
 
Semiconductor technology is at the heart of all modern vehicles. Their presence and prevalence have risen rapidly over the past couple of decades in the form of microcontrollers which now govern almost all aspects of vehicle operation. They communicate inputs, execute actuations and perform calculations across the entire car. This has transformed the public's perception of vehicles into "computers on wheels". Unsurprisingly, and as shown in the graphic below, automotive MCUs are the leading component for generating semiconductor value within the vehicle.
 
Semiconductor wafer value in the average vehicle today, and in 2033. Source: IDTechEx
 
IDTechEx's "Semiconductors for Autonomous and Electric Vehicles 2023-2033" report finds that the value of MCUs within vehicles is going to continue to grow. This will contribute to a wafer revenue CAGR of 9.4%, but much of the growth is going to be driven by growing semiconductor demand within advanced driver assistance systems (ADAS), autonomous vehicles (AV) and vehicle electrification. Not only will these new components require additional MCUs, but the advanced and intensive processing undertaken in automated driving is seeing the adoption of more cutting-edge semiconductor technologies into the vehicle.
 
Semiconductors for ADAS and autonomous vehicles, a rapidly growing sector
ADAS and autonomous vehicles promise to revolutionise the transportation industry with the superhuman safety they can offer. Providing these superhuman capabilities are a suite of sensors and computers that rely on advanced semiconductor technologies to function and provide the best performance. As such ADAS and autonomous vehicles are going to be a great boon to the automotive semiconductor market. According to the findings of this report the semiconductor wafer revenue for ADAS and AV applications will grow at a 10-year CAGR of 29%. There are three factors that combine to drive this high growth rate:
  1. The emergence and adoption of SAE level 3 and SAE level 4 autonomous vehicles and the additional sensors required.
  2. Automotive sensors transitioning to more advance semiconductors.
  3. High performance computing coming to vehicles.
 
This report explains all these trends in detail and their impact on the semiconductor markets. Of particular interest is the growth of non-silicon-based semiconductor demand driven by LiDAR. Most LiDARs today operate in the near infrared (NIR) region with a typical wavelength of 905nm, which can be achieved with silicon photodetectors. However, the future of LiDAR is likely to use the shortwave infrared (SWIR) region with a typical wavelength of 1,550nm. This trend within the industry is demonstrated by the overwhelming dominance of 1,550nm LiDAR announcements shown in the chart below. Details pertaining to the superiority of 155nm LiDARs and the impact the switch has on changing demand across different semiconductor technologies are covered in this report.
 
Source: IDTechEx
 
While Tesla has been publicly anti-lidar, other key players in the autonomy space such as Waymo, Cruise, Daimler and Honda are all using LiDAR on their highly automated vehicles. In fact, as of the end of 2022 there have only been two vehicles certified for SAE level 3 use (where the driver's attention is not required under certain conditions) on the road; the Mercedes S-Class and the Honda Legend. IDTechEx is expecting many more high-end vehicles to follow the S-Class over the next 10-years, and for level 3 technologies to be widely available. This will of course drive semiconductor demand across all the sensor types and computers that are needed for these highly advanced vehicles. But another major trend in the automotive market that will impact semiconductor demand is electrification.
 
Semiconductors for automotive electrification
The automotive industry is under increasing pressure to decarbonise through electrification and In 2022 electric vehicles (EV) sales rose to approximately 10% of all new vehicle sales. EV's are now heading out of the early adopter phase and towards the early majority and wider spread adoption. EVs, their power electronics and their battery packs bring additional demands that drive more growth within the semiconductor industry.
 
OEMs are always looking for ways to extend range by making the vehicles more efficient and one avenue increasing in popularity is moving from inverters based on silicon to ones based on silicon carbide There are two factors that are pushing electric vehicle OEMs such as Tesla, Mercedes, Audi and Ford towards silicon carbide. Firstly, some OEMs are planning to transition from 400V to 800V architectures. The higher voltage reduces the amount of current required to achieve the same power, this means reduced wastage in the powertrain system from Ohmic losses and increased efficiency. Silicon carbide is much more suited to the higher voltage and is therefore the more sensible choice than Si. However, and the second reason for adoption, silicon carbide is also more efficient than Si at 400V, which is why players like Tesla are interested even though it would struggle to transition to 800V with its existing 400V supercharger network. This report covers the pros and cons of silicon, silicon carbide and the even more nascent gallium nitride, and explains how these new technologies are going to impact the semiconductor wafer market.
 
The trends mentioned here are forecasted over a 10-year period to 2033 giving wafer volumes, revenues and raw material demand over ADAS and AV, electrification communication and infotainment and vehicle MCUs. For even more granular detail a database with over 400 forecast lines is available with this report. It covers 18 components, across four key vehicle areas, and considering four levels of automation and three different powertrain types (ICE, EV and PHEV), providing wafer volumes, revenues, raw material demand and more.
 
Key aspects
Technology trends that will impact semiconductor demand
  • Supply and value chain structure
  • Analysis of technology trends from key semiconductor players and automotive strategy for keeping up with latest advancements
  • Detailed overview of where semiconductor products are used in the driver assistance and automated driving systems
  • Trends in sensors that will change the demand for different semiconductor technologies in the future
  • Trends in electrification that will shift demand from Si to SiC and GaN in the future
  • Overview of vehicle communication and in-cabin trends
 
Market Forecasts:
10-year granular market forecasts of
  • 300mm equivalent wafer volumes (Si, InP, GaN and more)
  • Semiconductor wafer revenue (Si, InP, GaN and more)
  • Raw material demand for Si, In, P, Ga, Ge and more
 
10-year market forecasts split by
  • SAE autonomous level (0-2, 3, 4, 4 - robotaxis)
  • ADAS and autonomous end-point technology (radar, LiDAR, camera, MCUs)
  • Electrification (BEV vs PHEV)


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Table of Contents

1. EXECUTIVE SUMMARY
1.1. Introduction
1.2. Report scope
1.3. Accompanying database with more than 400 forecast lines
1.4. Where semiconductors are found in vehicles
1.5. MCU count on vehicles of the future
1.6. Semiconductor makers and key terminology
1.7. Top-down wafer market size estimate
1.8. Foundry technologies over time
1.9. SAE Levels of Automation in Cars
1.10. ADAS adoption
1.11. Semiconductors in ADAS systems
1.12. Robotaxis and mobility as a service coming soon
1.13. Semiconductors in autonomous systems
1.14. Semiconductor suppliers by ADAS/AD Component
1.15. MCU characteristics
1.16. High performance computers for automotive
1.17. Computational efficiency
1.18. Radar in automotive
1.19. Radar anatomy and semiconductor impacting trends
1.20. Transceivers Semiconductor Trends: Virtual Channels
1.21. Automotive radar trending towards more advanced silicon
1.22. Automotive LiDARs
1.23. Semiconductors in LiDAR
1.24. LiDAR trends impacting semiconductor demand
1.25. Cameras in ADAS and AV systems
1.26. 300mm silicon wafers forecast for ADAS and AV - 2023-2033
1.27. Non silicon semiconductors for ADAS and AV forecast - 2023-2033
1.28. Semiconductor wafer revenue for ADAS and AV applications forecast - 2023-2033
1.29. EV power electronics trends impacting semiconductors
1.30. The rise of electric vehicles- 2023-2033
1.31. Semiconductors in BMS core hardware
1.32. Vehicle automation and electrification doubles semiconductor value in vehicles
1.33. CHIPS acts to improve automotive shortages
1.34. 300mm semiconductor wafers for electrification forecast - 2023-2033
1.35. Revenue from semiconductor wafers in electrification forecast - 2023-2033
1.36. Total automotive semiconductor wafer demand forecast - 2023-2033
1.37. Semiconductor mineral demand forecast for automotive - 2023-2033
1.38. Semiconductor wafer revenue forecast across automotive industry - 2023-2033
1.39. 24 included company profiles
2. SEMICONDUCTOR PRODUCTION AND SUPPLY CHAIN
2.1. Overview
2.1.1. From raw material to product
2.1.2. Supply chain
2.1.3. Making smaller chips, greater yields
2.1.4. Semiconductor value chain
2.1.5. Semiconductor company in-house abilities
2.1.6. Even split between company types
2.1.7. Company locations
2.1.8. Semiconductor foundry in-house technologies
2.1.9. Trend toward fabless tier 2s for high performance.
2.1.10. Companies outsourcing to TSMC
2.1.11. Shortages
2.1.12. Top-down wafer market size estimate
2.1.13. Increasing supply - Infineon's new Villach site
2.1.14. Increasing supply - Texas Instruments new fab in Sherman, Texas
2.2. Trends from the chip makers, next gen transistors, and technology roadmaps.
2.2.1. The drive for smaller node technologies
2.2.2. Key parameter of growth for processor and memory (1)
2.2.3. Key parameter of growth for processor and memory (2)
2.2.4. The economics of scaling
2.2.5. Foundry technologies over time
2.2.6. Routes to increase I/O density
2.2.7. Semiconductor foundries and their roadmap
2.2.8. Cutting edge for automotive
2.2.9. Transistor device development (1)
2.2.10. Transistor device development (2)
2.2.11. Key parameters for transistor device scaling
2.2.12. Evolution of transistor device architectures
2.2.13. CNTs for transistors
2.2.14. CNFET research breakthrough (1)
2.2.15. CNFET research breakthrough (2)
2.2.16. CNFET case study (1)
2.2.17. 3D SOC
2.2.18. On-chip memory
2.2.19. Routes to increase I/O density
2.2.20. Advanced technologies for automotive
3. SEMICONDUCTORS FOR ADAS SENSORS, AUTONOMOUS VEHICLE SENSORS AND HIGH-PERFORMANCE COMPUTING IN VEHICLES
3.1. Introduction to ADAS and AV
3.1.1. SAE Levels of Automation in Cars
3.1.2. Functions of Autonomous Driving at Different Levels
3.1.3. Adoption of ADAS (1)
3.1.4. Adoption of ADAS (2)
3.1.5. Safety Mandated Features Driving Wider Radar Adoption.
3.2. ADAS and autonomous vehicle sensor suites
3.2.1. Semiconductors in the ADAS system
3.2.2. Semiconductors in ADAS systems
3.2.3. Level 2 senor suite and semiconductors
3.2.4. Semiconductors in autonomous systems
3.2.5. SAE level 3 sensor suite and semiconductors
3.2.6. Level 4 private: The Trifactor
3.2.7. Level 4 MaaS: The Trifactor
3.2.8. ADAS products - example product page
3.2.9. Level 2 - purchasing systems not components
3.2.10. Case study - Tesla
3.2.11. Case study - Audi A8 (2017)
3.2.12. Case study - Honda Legend
3.2.13. Case study - Mercedes S-Class (2021)
3.2.14. Case study - VW Golf (2021)
3.2.15. Case study - Lexus LS, Toyota Mirai (2021)
3.2.16. Robotaxi case study - Waymo
3.2.17. Robotaxi case study - Cruise
3.2.18. Robotaxi case study - AutoX
3.2.19. Baidu/Apollo Sensor Suite
3.2.20. Aurora Sensor Suite
3.3. Semiconductors used for radar
3.3.1. Front Radar Applications
3.3.2. The Role of Side Radars
3.3.3. Radar Anatomy
3.3.4. Radar Board Trends
3.3.5. The trend towards smaller transistors
3.3.6. Transceivers Semiconductor Trends: Power and Noise
3.3.7. Transc

 

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