20210616-瑞士信贷集团-China_Auto_LiDAR_industry_A_promising_sensor_for_vehicle_Autonomy_36页_2mb

Summary of China Auto LiDAR Industry

Core Content

LiDAR (Light Detection and Ranging) is a critical sensor for high-level vehicle autonomy (Level 3 and Level 4) due to its high-resolution 3D sensing capabilities, superior precision, and performance in low-light conditions. It is more detailed than millimeter-wave radar and less affected by weather than cameras.

Main Viewpoints

• LiDAR's Role in Autonomy: LiDAR provides detailed 3D point cloud data without significant backend processing. It is essential for high-level autonomy, enabling vehicles to perceive and navigate complex environments, such as urban areas.

• Structural Growth Drivers:

  • Penetration of Autonomous Driving: The penetration of Level 2 and above autonomous driving systems is expected to rise from 12% in 2020 to 60% by 2025, and 100% in 2030.
  • Cost Reduction: LiDAR average selling price is projected to decline from Rmb7,000 in 2020 to Rmb1,200 in 2025, and Rmb600 in 2030, driven by economies of scale, technological innovation, and integration of components into single chips.
  • Solid-State LiDAR Maturity: Solid-state designs (e.g., OPA and Flash) are becoming more mature and cost-effective, offering advantages in reliability and size.

• Market Outlook:

  • China's auto-related LiDAR sales volume is expected to grow at a 9-year CAGR of 85%, reaching 86 million units by 2030.
  • Sales revenue is projected to reach Rmb32 billion (US$5 billion) in 2025 and Rmb51.5 billion (US$8 billion) in 2030.

• LiDAR Adoption in Chinese Smart EV Makers:

  • Companies like NIO, Xpeng, and Li Auto have already introduced Level 3 autonomous driving features, using LiDAR to enhance perception capabilities in urban environments.
  • Chinese LiDAR suppliers benefit from mature scanning technology, enabling faster mass production and supporting smart EVs in solidifying their leadership in autonomy.

Key Information

• LiDAR Components:

  • Transceiver Module: Includes laser transmitter (EEL or VCSEL) and receiver (PIN, APD, SPAD, SiPM).
  • Scanning Module: Uses mechanical (rotating polygon, prism, galvanometer) or solid-state (MEMS, Flash, OPA) methods.
  • Logic Chip Module: Processes data to generate point clouds, with options including FPGAs, ASICs, and SoCs.

• LiDAR vs. Radar and Camera:

  • Camera: Cost-effective, good for color and text recognition, but limited in depth perception and weather performance.
  • Radar: Robust in bad weather, but lacks resolution and 3D detection capability.
  • LiDAR: Offers high-resolution 3D mapping, better performance in low light, and is considered essential for Level 3 and Level 4 autonomy.

• Sensor Placement and Specifications:

  • Front LiDARs require long range and high resolution for highway use.
  • Side, corner, and rear LiDARs need wider FOV for urban navigation.
  • Examples: Xpeng P5 uses two rotating prism LiDARs for wide FOV; NIO ET7 uses an ultra-long range LiDAR with 500m detection distance and 120° FOV.

• Stock Ideas:

  • Preferred: NIO, Xpeng, Li Auto, and Great Wall Motor due to their early LiDAR adoption, leadership in Level 3 autonomy, and clear plans for Level 4.
  • Conservative: SOE auto makers like BAIC and Brilliance due to potential competition from intelligent vehicles.
  • Target Price Adjustments: Li Auto's target price is raised to US$38 from US$31.

Autonomous Driving Classification

Penetration Rate Projections

• Level 2 and above: 12% in 2020 → 60% in 2025 → 100% in 2030
• Level 3: 1% in 2020 → 14% in 2025 → 63% in 2030
• Level 4: 0.1% in 2022 → 3% in 2025 → 23% in 2030

Strategic Advantages of China in Autonomous Driving

• Market Size: Largest auto market globally.
• Technology: 5G, V2X infrastructure, Beidou satellite system.
• Smart City Development: Supports the growth of autonomous driving ecosystems.

Conclusion

The Chinese auto LiDAR industry is poised for significant growth, driven by increasing adoption of high-level autonomy, falling LiDAR costs, and technological advancements. Chinese smart EV makers are well-positioned to leverage this trend, with a focus on LiDAR integration to enhance their autonomy capabilities and compete globally.