新兴车企战略分析（2022）：理想汽车

理想汽车2022年上半年销量60801辆，同比增长99.1%。 从车型来看，丽ONE上半年依然是主力。 随着2022年9月L8的上市，相信Li ONE将逐渐退出生产线，L8、L7、L9成为未来产销重心。

本报告重点关注中国新兴汽车製造商理想汽车，提供有关公司概况、近期业绩趋势、营销和服务结构、应用、电气技术、电气和电子架构等增长的信息。

内容

新兴汽车製造商销量前 10 名（2021 年）

第 1 章 Li 汽车简介

• 基本信息
• 开发成果
• 收入、销量、计划
• 汽车製造平台和产品规划
• 财务结果
• 投资结果
• 研发投资和方向
• 生产布局
• 营销服务

第2章理想汽车App用户操作

• 理想汽车应用版本迭代（一）
• 理想汽车应用版本迭代（2）
• 理想汽车应用版本迭代（3）
• 首页用户画像分析
• 功能板块分析——社区板块/新闻板块
• 功能板分析 - 车辆控制板
• 功能板块分析-理想汽车商城产品类别/特点
• 功能板分析 - 我的板
• 管理策略/用户增长系统
• 用户增加系统-积分功能及获取方式
• 用户增值系统-积分消费模式
• 用户增长系统 - 徽章/会员等级

第三章理想汽车电气技术

• 比较销售模型之间的动态性能参数
• 电气技术布局
• 电力系统特点
• 第一代车辆增程式电气解决方案
• 第二代汽车增程式电气解决方案
• Li ONE热管理系统架构及供应商
• Li ONE 的热管理系统策略
• Li L9 热管理系统和驱动系统供应商
• 车辆供能方式
• 超级充电网络规划
• 电气化动态

第4章锂汽车电子电气结构

• EEA 演变：LEEA 1.0 到 LEEA 3.0
• LEEA 2.0 硬件架构：AD Max
• LEEA 2.0 硬件架构：自动驾驶算法
• LEEA 2.0 硬件架构：智能座舱
• LEEA 2.0 硬件架构：中央域控制器 (XCU)
• LEEA 2.0 硬件架构：中央计算平台 + 4 个区域控制器
• LEEA 3.0 硬件架构：中央计算机单元 (CCU) (1)
• LEEA 3.0 硬件架构：中央计算机单元 (CCU) (2)
• LEEA 3.0 硬件架构：区域控制器
• LEEA 3.0 通信架构：PCIe 交换机、TSN 交换机
• LEEA 3.0 软件架构：定义和部署多级服务
• LEEA 3.0 软件架构：LiOS (Li Auto OS)

第五章理想汽车智能驾驶技术

• 自动驾驶发展路线图
• 自动驾驶芯片布局
• 智能驾驶研发模式
• 智能驾驶算法（一）
• 智能驾驶算法（二）
• 智能驾驶数据的积累和处理
• AD系统及典型模型
• 广告最大系统
• AD Pro 系统
• ADAS 硬件迭代和供应商
• ADAS 硬件 - 在 LiDAR 解决方案中比较蔚来汽车、理想汽车和小鹏汽车
• ADAS 的软件迭代
• ADAS - NOA 功能
• ADAS - 比较 NOA 解决方案中的蔚来汽车、理想汽车、小鹏汽车和特斯拉
• 自动泊车系统发展路线图
• 自动泊车的功能演变
• 全场景可视化泊车
• 自动驾驶中的合作动力学

第6章理想汽车的智能座舱与车联网技术

• OTA更新模式
• OTA 更新分析 - 按频率
• OTA 更新分析 - 按年份
• OTA 更新分析 - 按类别
• OTA 更新的主要变化 (1)
• OTA 更新的重大变化 (2)
• OTA更新计划
• 智能座舱配置
• L9、L8 和 L7 的座椅配置
• 李艾
• 李艾互动（一）
• 李艾互动（二）
• 李艾互动（3）
• 李爱的应用实例：L9
• 其他智能座舱供应商
• 智能座舱研发计划
• 智能语音系统
• 汽车生态学
• 车联网安全实践
• IoV 中的合作动力学

Research on Emerging Automaker Strategy: the strategic layout of Li Auto in electric vehicles, cockpits and autonomous driving

Li Auto will shift from the single extended-range route to the "extended-range + high-voltage battery-electric" route of in 2023.

In the first half of 2022, Li Auto sold 60,801 vehicles, up 99.1% year-on-year. In terms of models, Li ONE still played a main role in the first half of the year. With the launch of L8 in September 2022, Li ONE will be gradually withdrawn from the production line, while L8, L7 and L9 will be the focus of production and marketing in the future.

As for product planning, all the models currently being sold by Li Auto are extended-range electric vehicles. However, Li Auto plans to launch at least two high-voltage battery-electric vehicles every year from 2023 onward. For the purpose of high-voltage super-fast charging, Li Auto deploys the following four aspects: First, 4C batteries. Second, application of SiC technology. Third, thermal management system. Fourth, 400KW charging network.

According to its plan, Li Auto will produce the third-generation semiconductor SiC power chip in 2024. At the same current of the high-voltage platform, this chip is 70% smaller than an IGBT chip, with the comprehensive efficiency being improved by 6%. The layout of Li Auto's 800V high-voltage battery-electric technology reveals that one of the selling points of new cars in the future will be reflected in the charging speed.

Li Auto has self-developed AEB and NOA and laid out autonomous driving chips to progress on intelligent driving

As for the progress of intelligent driving, Li Auto has developed AEB system by itself as a "latecomer". In the future, Li Auto will provide all open source codes of its AEB system to improve traffic safety.

In addition, Li Auto added NOA to 2021 Li ONE in December 2021, improved the performance of AEB, and optimize the detection and fusion of cameras and radar. Since 2022, all new cars have been equipped with Li Auto's self-developed hardware compatible with L4 autonomous driving as standard. Li Auto plans to make urban NGP functions available in Li L9 through OTA in 2023, and install L4 autonomous driving capability on production vehicles via OTA around 2024.

Regarding the core underlying technology layout of intelligent driving, Li Auto established Sichuan Lixiang Intelligent Technology Co., Ltd. in May 2022 to design chips. In August 2022, Xie Yan, the former vice president of Huawei Software, joined Li Auto as the head of system R&D division. The system R&D division is mainly responsible for R&D of some underlying intelligent technologies, including Li Auto's self-developed operating system and computing platform. Li Auto's computing platform business also includes its self-developed intelligent driving chip project.

For the intelligent driving algorithm, Li Auto uses BEV framework similar to that of Tesla, that is, it utilizes pure vision for motion perception prediction. On the basis of BEV visual information, Li Auto exploits additional LiDAR and HD map information input to implement the BEV fusion algorithm, and adds a visual security module and a LiDAR security module which are redundant with BEV framework model for the sake of an extra layer of protection.

The cockpit of Li Auto upgrades from 2D interaction to 3D interaction.

The cockpit multi-modal interaction represents development trend of human-machine co-driving era. As per three new cars launched in 2022, Li Auto upgrades the past four-screen 2D interaction in Li ONE to current five-screen 3D interaction, and realizes "voice+gesture" multi-modal interaction.

For example, the five screens of Li L9 include a safe driving interactive screen, a W-HUD with a projected area of 13.35 inches, a 15.7-inch integrated center console screen and co-driver screen, and a 15.7-inch rear entertainment screen. The in-vehicle 3D ToF sensor perceives the cockpit environment in real time. Plus, 6 microphones, 7.3.4 panoramic sound layout, 5G dual-operator automotive communication network, and multi-modal spatial interaction technology developed by Li Auto based on deep learning enable the three-dimensional interaction in the cockpit.

In terms of perception, Li AI, the intelligent cockpit space, imitates the coordination of human ears and eyes to attain the three-dimensional information perception inside the vehicle under the influence of multi-modal attention technology by a distributed hexasilicon microphone, an IR 3D ToF sensor, MIMO-Net six-vocal-range enhancement network and MVS-Net multinocular & multi-view visual fusion network.

As for understanding and expression, Li AI restores the multi-source heterogeneous data sensed by fusion perception to concrete events in the network, and fulfills further abstract understanding. Ultimately, knowledge linking, knowledge completion and logical reasoning form an event graph, allowing machines to have their own understanding and decision-making capabilities.

Regarding voice technology, Li Auto defines its voice assistant "Lixiang Tongxue" as the user's housekeeper (current stage) and family (future goal), and plans a three-stage product upgrade. At present, the goals of the first two stages have been achieved through OTA: The first stage: Li Auto's self-developed "Lixiang Tongxue" engine replaces the underlying capabilities with Horizon + AIspeech + Microsoft, etc.

The second stage: "what you see is what you can say", four-vocal-range locking and other functions.

In the future, the voice system will offer functions such as "from application-on-demand to network-on-demand", cross-screen multi-person dialogue, and "the front passenger can pick up the conversation after the driver finishes speaking".

Table of Contents

Top10 Emerging Automakers by Sales Volume in 2021

1 Profile of Li Auto

• 1.1 Basic Information
• 1.2 Development History
• 1.3 Revenue, Sales Volume and Planning
• 1.4 Carmaking Platform and Product Planning
• 1.5 Financing History
• 1.6 Investment History
• 1.7 R&D Investment and Direction
• 1.8 Production Layout
• 1.9 Marketing and Services
  • 1.9.1 Sales Models
  • 1.9.2 Distribution of Offline Service Outlets
  • 1.9.3 Sales Channels
  • 1.9.4 After-sales Services
  • 1.9.5 Financial Solutions

2 User Operation of Li Auto APP

• 2.1 Version Iteration of Li Auto APP (1)
• 2.1 Version Iteration of Li Auto APP (2)
• 2.1 Version Iteration of Li Auto APP (3)
• 2.2 User Portrait and Homepage Analysis
• 2.3 Functional Plate Analysis - Community Plate and News Plate
• 2.4 Functional Plate Analysis - Vehicle Control Plate
• 2.5 Functional Plate Analysis - Commodity Categories and Characteristics of Li Auto Mall
• 2.6 Functional Plate Analysis - My Plate
• 2.7 Operation Strategy and User Growth System
• 2.8 User Growth System - Points Features and How to Obtain Them
• 2.9 User Growth System - Points Consumption Modes
• 2.10 User Growth System - Badges and Membership Levels

3 Electric Technology of Li Auto

• 3.1 Comparison between Models on Sale in Dynamic Performance Parameters
• 3.2 Electric Technology Layout
• 3.3 Features of Power System
• 3.4 The First-generation Extended-range Electric Solution for Vehicles
• 3.5 The Second-generation Extended-range Electric Solution for Vehicles
• 3.6 Thermal Management System Structure and Suppliers of Li ONE
• 3.7 Thermal Management System Strategy of Li ONE
• 3.8 Thermal Management System and Drive System Suppliers of Li L9
• 3.9 Energy Supplement Modes of Vehicles
• 3.10 Super Charging Network Planning
• 3.11 Electrification Dynamics

4 Electronic and Electrical Architecture of Li Auto

• 4.1 Evolution of EEA: LEEA 1.0-LEEA 3.0
• 4.2 LEEA 2.0 Hardware Architecture: AD Max
• 4.3 LEEA 2.0 Hardware Architecture: Autonomous Driving Algorithm
• 4.4 LEEA 2.0 Hardware Architecture: Intelligent Cockpit
• 4.5 LEEA 2.0 Hardware Architecture: Central Domain Controller (XCU)
• 4.6 LEEA 2.0 Hardware Architecture: Central Computing Platform +4 Zonal Controllers
• 4.7 LEEA 3.0 Hardware Architecture: Central Computer Unit (CCU) (1)
• 4.8 LEEA 3.0 Hardware Architecture: Central Computer Unit (CCU) (2)
• 4.9 LEEA 3.0 Hardware Architecture: Zonal Controller
• 4.10 LEEA 3.0 Communication Architecture: PCIe Switch and TSN Switch
• 4.11 LEEA 3.0 Software Architecture: Definition and Deployment of Multi-level Services
• 4.12 LEEA 3.0 Software Architecture: LiOS (Li Auto OS)

5 Intelligent Driving Technology of Li Auto

• 5.1 Autonomous Driving Development Roadmap
• 5.2 Autonomous Driving Chip Layout
• 5.3 Intelligent Driving R&D Model
• 5.4 Intelligent Driving Algorithm (1)
• 5.4 Intelligent Driving Algorithm (2)
• 5.5 Intelligent Driving Data Accumulation and Processing
• 5.6 AD System and Typical Models
• 5.7 AD MAX System
• 5.8 AD Pro System
• 5.9 Hardware Iteration and Suppliers of ADAS
• 5.10 ADAS Hardware - Comparison between NIO, Li Auto and Xpeng in LiDAR Solutions
• 5.11 Software Iteration of ADAS
• 5.12 ADAS - NOA Functions
• 5.13 ADAS - Comparison between NIO, Li Auto, Xpeng and Tesla in NOA Solutions
• 5.14 Development Roadmap of Autonomous Parking System
• 5.15 Functional Evolution of Automated Parking
• 5.16 Visual Parking at All Scenarios
• 5.17 Dynamics of Cooperation in Autonomous Driving

6 Intelligent Cockpit and IoV Technology of Li Auto

• 6.1 OTA Update Modes
• 6.2 OTA Update Analysis - by Frequency
• 6.3 OTA Update Analysis - by Year
• 6.4 OTA Update Analysis - by Category
• 6.5 Major Changes in OTA Updates (1)
• 6.5 Major Changes in OTA Updates (2)
• 6.6 OTA Update Plan
• 6.7 Intelligent Cockpit Configuration
• 6.8 Seating Configuration of L9, L8 and L7
• 6.9 Li AI
• 6.10 Li AI Interaction (1)
• 6.10 Li AI Interaction (2)
• 6.10 Li AI Interaction (3)
• 6.11 Example of Li AI Application: L9
• 6.12 Other Intelligent Cockpit Suppliers
• 6.13 Intelligent Cockpit R&D Planning
• 6.14 Intelligent Voice System
• 6.15 Automotive Application Ecology
• 6.16 Actual IoV Security
• 6.17 Dynamics of Cooperation in IoV