자동차 지능형 진단 산업(2026년)

Automotive Intelligent Diagnosis Research: Powered by AI, Remote Diagnosis Is Being Upgraded towards Intelligence.

ResearchInChina released the Automotive Intelligent Diagnosis Industry Report, 2026. This report summarizes the development characteristics of market segments in terms of automotive remote diagnosis, intelligent upgrading, after-sales diagnosis, engineering diagnosis, production line diagnosis, knowledge graph and AI large model application, data collection and data standardization. It also compares and analyzes OEMs' application of intelligent diagnosis systems, installation in vehicle models, and patent layout, and the business layout, characteristics and product advantages of suppliers in the intelligent diagnosis sector.

I. In 2025, the Installation Rate of Automotive Remote Diagnosis was 54.4%, ABUP Leading with A 39.5% Share.

Automotive remote diagnosis refers to the function of remotely troubleshooting vehicle faults based on vehicle self-inspection function combined with network communication technology. According to the Automotive Intelligent Diagnosis Industry Report, 2026 by ResearchInChina, the installation of remote diagnosis functions in passenger cars in China has accelerated in recent years.

In 2025, remote diagnosis functions were installed in over 12 million passenger cars in China, a year-on-year increase of 14.8%; the installation rate reached 54.4%, up by 6.8 percentage points compared with the end of 2024. New energy vehicles recorded a higher installation rate. In 2025, remote diagnosis functions were installed in 8.204 million new energy passenger cars in China, up by 21.8% year on year; the installation rate stood at 71.8%, an increase of 3.6 percentage points from the end of 2024.

Remote diagnosis mainly takes two forms: in-house development by OEMs, and third-party suppliers. In 2025, 56.4% of passenger car remote diagnosis systems in China were provided by third-party suppliers, and 32.9% were developed in-house by OEMs. Third-party suppliers dominate the market with flexible and rapidly deployable customized platform solutions.

Among third-party suppliers providing remote diagnosis services in 2025, ABUP ranked first with a 39.5% share, while Desay SV and Carota took the second and third places with 14.0% and 13.8% shares respectively. In addition, Huawei, ExceedData, and Excelfore among others have achieved growing market shares by taking advantage of industrial, data platform, OTA technology, etc.

II. Remote Diagnosis Becomes A Powerful Tool for OEMs to Reduce Costs and Improve Efficiency.

Supported by the Internet of Vehicles and cloud AI technologies, automotive remote diagnosis systems enable real-time vehicle condition monitoring, fault prediction, remote repair and precise task assignment. They have become a core tool for enterprises to reduce after-sales service costs, improve operational efficiency and enhance customer satisfaction.

Whether luxury brands (Mercedes-Benz, BMW, Li Auto), mid-to-high-end brands (Tesla, Xpeng) or economy brands (BYD, SAIC-GM-Wuling), all are reconstructing their after-sales service systems through remote diagnosis systems to boost customer satisfaction and economic benefits.

Tesla: Remote Diagnosis Have Solved A Total of Over 200,000 Issues.

As a typical mid-to-high-end brand, Tesla took the lead in launching intelligent after-sales service as early as 2018, realizing remote repair for vehicle faults or offline service appointment and resource allocation. It also accelerates automatic vehicle update, diagnosis and repair. With OTA technology and vehicle owner authorization, the intelligent backend of Tesla's Remote Service Center can remotely fix vehicle faults.

Through its intelligent diagnosis center, Tesla has remotely solved more than 200,000 problems, saving a total of about 250,000 hours of waiting time for in-store customers. In the past year, Tesla China's after-sales service centers boasted a one-time repair rate of 97.4%, and a user feedback satisfaction of still over 98%.

Xpeng Motors: Remote Diagnosis + Graded Warning to Improve After-sales Efficiency

Targeting the mid-to-high-end market as an Internet-based auto brand in China, Xpeng has independently developed an intelligent remote diagnosis system for after-sales services, providing remote backend diagnosis of vehicle faults and continuous OTA updates, allowing users to solve problems without visiting stores.

The intelligent remote diagnosis platform issues safety-graded warnings for vehicle faults. Remote technical engineers quickly locate faults and take countermeasures according to system prompts to ensure driving safety. On this basis, automakers or dealers can remotely diagnose vehicle problems via the platform and fix some software issues remotely or through software upgrades.

Differing from traditional after-sales services needing the long waiting time for spare parts, intelligent remote diagnosis allows automakers or dealers to confirm maintenance plans in advance and prepare required spare parts and service bays, saving valuable time for vehicle owners.

BYD: Remote Diagnosis Covers Most Models in Dynasty and Ocean Series.

As an economy new energy vehicle brand, most models of BYD are priced below 200,000 yuan. At present, most models in BYD's Dynasty and Ocean series support remote diagnosis.

Every time the vehicle is powered on, BYD's control system conducts a range of self-inspections on the voltage, current, temperature, position, speed, pressure, signals and other parameters of each component to judge and update the status of relevant parts.

When a vehicle fault occurs, BYD's Cloud Diagnosis Center can remotely read fault codes with the owner's authorization, and guide the owner to troubleshoot through simple operations (such as starting the engine in place), avoiding the trouble of traveling to repair shops.

After remote diagnosis, service shops evaluate whether the vehicle needs in-store maintenance according to the fault, and output a diagnosis opinion. If in-store service is unnecessary, the system can solve the problem remotely or guide the customer through simple operations, reducing unnecessary travel and time waste.

Remote diagnosis service makers diagnosis the consultation process up-front and intelligent. Service consultants and maintenance personnel can learn about vehicle problems and maintenance items in advance, and prepare corresponding spare parts before the vehicle arrives at the store, effectively avoiding stockouts and reducing waiting time for vehicle reception and maintenance.

SAIC-GM-Wuling: Remote Diagnosis Widely Covers Models with Silver Wuling Logo, Upgrading to Intelligent Diagnosis.

As a typical economy car brand, most vehicle models of Wuling are priced below 100,000 yuan. Wuling is an industry leader in deployment of remote diagnosis functions, which have been widely applied to its silver logo models.

From 2021 to 2025, SAIC-GM-Wuling integrated remote diagnosis into its "Smart Service" program. Relying on 24/7h real-time Internet of Vehicles big data, it proactively provides services when users operate improperly or vehicles break down, realizing proactive and efficient after-sales repair and service, and a fundamental upgrade of the service model. From "post-fault repair" to "pre-fault warning", SAIC-GM-Wuling's Smart Service has achieved up-front services and experience upgrading.

In 2026, SAIC-GM-Wuling's remote diagnosis service will upgrade to intelligent diagnosis. Based on a knowledge reasoning-driven intelligent diagnosis engine, it integrates knowledge graphs and AI large models to build an expert-level interactive assistant, further enhancing the intelligence of the diagnosis system.

III. Driven by AI, Remote Diagnosis Realizes Intelligent Upgrade.

Driven by AI, big data, vehicle-cloud collaboration, 5G communication and other technologies, automotive remote diagnosis is upgrading to more intelligent, predictive and efficient intelligent diagnosis. On the one hand, the in-depth integration of computing power, algorithms and data enables diagnosis systems to leap from "passive response" to "predictive maintenance". On the other hand, with the application of AI technologies, intelligent diagnosis systems continue to evolve in terms of autonomous fault location and proactive solution promotion.

Leading suppliers such as ABUP and Huawei are working on intelligent upgrading of remote diagnosis using AI technologies (especially AI large models).

ABUP: Introducing AI Large Model + Knowledge Base Dual Engine to Build a New-Generation Intelligent Diagnosis Platform

ABUP deeply integrates its capabilities in remote diagnosis, OTA, software platform management, data management and other aspects with AI to build a new-generation intelligent diagnosis platform.

Key FEATURES of ABUP's Intelligent Diagnosis Platform

Uses a dual engine combining large models and knowledge graphs to build a comprehensive and detailed automotive fault knowledge base.

Integrates multi-source data such as discrete vehicle information, fault information and maintenance cases organically using new-generation LLM and RAG technologies to form a structured and semantic knowledge network.

Effectively maintains signals, data, models and diagnosis strategy logic, and closely connects various models, remote tools and systems through knowledge graphs, embedding intelligent diagnosis functions into every link.

At present, ABUP has undertaken knowledge graph implementation projects for multiple automakers, and its intelligent diagnosis system has empowered multiple OEMs including SAIC-GM-Wuling.

Huawei: Yunque Large Model's Intelligent Diagnosis Location Accuracy of Core Components Hits 90%.

Huawei Qiankun Yunque Large Model is trained based on a foundation model with tens of billions of parameters, combined with its own TB-level fault diagnosis special corpus.

Core Features of Qiankun Yunque Large Model

Supports Q&A interaction. By inputting fault descriptions, the Yunque Large Model automatically understands problems through semantic analysis, conducts intelligent triage, formulates diagnosis schemes, and generates diagnosis conclusions and repair suggestions.

Full-process automated execution reduces the original hour-level diagnosis time to minutes, greatly improving diagnosis efficiency. In practical use, the intelligent diagnosis location rate of core components reaches 90%.

Equipped with a TB-level fault diagnosis corpus, 400+ special diagnosis algorithms and 4000+ signal second-level collection, it enables instant Q&A for users and full-process automatic diagnostic testing. It also provides full-process automatic intelligent diagnosis for vehicles.

Table of Contents

1 Overview of Automotive Intelligent Diagnosis

• 1.1 Definition of Automotive Intelligent Diagnosis
• 1.2 Development History of Automotive Intelligent Diagnosis
• 1.3 Application Scenarios of Intelligent Diagnosis
• 1.4 Industrial Chain of Intelligent Diagnosis
• 1.5 Automotive Diagnosis Market Environment
  • 1.5.1 Mobile Phone Remote Control Market
  • 1.5.2 T-Box Market
  • 1.5.3 Cellular Vehicle-to-Everything (C-V2X) Communication Market
• 1.6 Automotive Diagnosis Policy Environment
• 1.7 Intelligent Diagnosis Standards and Specifications
• Technical Standards for Automotive Diagnosis (1)
• Technical Standards for Automotive Diagnosis (2)
• Technical Standards for Automotive Diagnosis (3)
• Technical Specifications for Automotive Maintenance, Inspection and Diagnosis
• 1.8 Specifications for Intelligent Diagnosis Interface Architecture
• Types of Diagnosis Interface Architecture
• Diagnosis Interface Architecture 1
• Diagnosis Interface Architecture 2
• Diagnosis Interface Architecture 3
• Diagnosis Interface Architecture 4
• 1.9 Intelligent Diagnosis Standard Protocols
  • 1.9.1 DoIP Standard
• DoIP Standard: Principles
• DoIP Standard: Relationship with OTA
• 1.9.2 UDS Standard
• UDS: Diagnosis Structure
• UDS: Service Identifiers and Codes
• UDS: Supported Diagnosis Functions
• UDS Application Cases
• 1.9.3 SOVD Standard
• SOVD Application Case 1
• SOVD Application Case 2
• SOVD Application Case 3
• 1.10 Core Value of Intelligent Diagnosis

2 Automotive Intelligent Diagnosis Market Segments

• 2.1 On-Board Diagnostics (OBD) and After-sales Diagnostic Instruments
• OBD Diagnosis
• OBD-II
• OBD Suppliers
• Features of After-sales Diagnostic Instruments
• Representative Products of After-sales Diagnostic Instruments
• Representative Product 1 of After-sales Diagnostic Instruments
• Representative Product 2 of After-sales Diagnostic Instruments
• Representative Product 3 of After-sales Diagnostic Instruments
• 2.2 Engineering Diagnostic Instruments
• Introduction to Engineering Diagnostic Instruments
• Representative Products of Engineering Diagnostic Instruments
• Representative Product 1 of Engineering Diagnosis
• Representative Product 2 of Engineering Diagnosis
• Representative Product 3 of Engineering Diagnosis
• Representative Product 4 of Engineering Diagnosis
• Representative Product 5 of Engineering Diagnosis
• 2.3 Production Line Diagnosis
• Introduction to Production Line Diagnosis
• Representative Products of Production Line Diagnostic Instruments
• ABUP's Production Line Diagnosis Tool
• AI Production Line Diagnosis of MMI INSTITUTE IX
• 2.4 Automotive Remote Diagnosis
• Features of Automotive Remote Diagnosis
• Remote Diagnosis System Architecture
• Remote Diagnosis Process and Functions
• Classification of Remote Diagnosis
• Global Automotive Remote Diagnosis Market: Market Size
• Global Automotive Remote Diagnosis Market: Application Scenarios
• Global Automotive Remote Diagnosis Market: Competitive Landscape
• China Automotive Remote Diagnosis Market: Installations and Installation Rate
• China Automotive Remote Diagnosis Market: Brand Characteristics
• China Automotive Remote Diagnosis Suppliers and Competitive Landscape
• Requirements of Remote Diagnosis for Cloud Platforms
• Remote Diagnosis/Cloud Diagnosis Layout of Major Suppliers
• Case 1
• Case 2
• Case 3
• 2.5 Data Collection and Data Governance
• Types of Automotive Big Data
• Big Data Application 1 in Remote Diagnosis
• Big Data Application 2 in Remote Diagnosis
• Diagnosis Data Collection Layout of Representative Enterprises
• Data Collection Case 1
• Data Collection Case 2
• Data Collection Case 3
• Data Collection Case 4
• Requirements of Intelligent Diagnosis for Data Governance
• Data Governance Solution 1 Supporting Fault Diagnosis
• Data Governance Solution 2 Supporting Fault Diagnosis
• Data Governance Solution 3 Supporting Fault Diagnosis
• Data Governance Solution 4 Supporting Fault Diagnosis
• Data Governance Solution 5 Supporting Fault Diagnosis
• Data Governance Solution 6 Supporting Fault Diagnosis
• 2.6 Intelligent Diagnosis of EIC Systems for New Energy Vehicles
• Fault Diagnosis of New Energy Vehicles
• Safety Risks of New Energy Vehicles
• Typical Risks of Power Battery System
• Battery Fault Characteristics
• Battery State of Health Estimation Methods
• Battery State of Health Estimation Methods
• Battery Fault Identification Methods
• Power Battery Fault Identification Method 1
• Power Battery Fault Identification Method 2
• EIC System Intelligent Diagnosis Case 1
• EIC System Intelligent Diagnosis Case 2
• EIC System Intelligent Diagnosis Case 3
• EIC System Intelligent Diagnosis Case 4
• EIC System Intelligent Diagnosis Case 5
• EIC System Intelligent Diagnosis Case 6
• 2.7 Intelligent Diagnosis Upgrade Capabilities
• Production Line Diagnosis Upgrade: Background
• Production Line Diagnosis Upgrade: Core Advantages
• Production Line Diagnosis Upgrade: Derived Value
• Vehicle Diagnosis Upgrade
• Vehicle Diagnosis Upgrade Layout 1 of Major Suppliers
• Vehicle Diagnosis Upgrade Layout 2 of Major Suppliers
• Vehicle Diagnosis Upgrade Layout 3 of Major Suppliers
• Vehicle Diagnosis Upgrade Layout 4 of Major Suppliers
• Vehicle Diagnosis Upgrade Layout 5 of Major Suppliers
• Vehicle Diagnosis Upgrade Layout 6 of Major Suppliers
• 2.8 Intelligent Diagnosis AI Large Model and Knowledge Graph
• Overview of Intelligent Diagnosis AI Large Models and Knowledge Graphs
• Intelligent Diagnosis AI Large Model and Knowledge Graph Layout of OEMs
• Intelligent Diagnosis AI Large Model and Knowledge Graph Layout of Suppliers
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 1
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 2
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 3
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 4
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 5
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 6
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 7
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 8
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 9
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 10
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 11
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 12
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 13
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 14
• Intelligent Diagnosis AI Large Model and Knowledge Graph Case 15

3 Intelligent Diagnosis Layout of OEMs

• 3.1 Internet-based Auto Brands
  • 3.1.1 Xpeng Motors
• Xpeng Motors: Features of Intelligent Diagnosis
• Xpeng Motors: AI Diagnosis Platform
• 3.1.2 NIO
• NIO: Features of Intelligent Diagnosis
• NIO: AI Diagnosis
• 3.1.3 Xiaomi Auto
• Xiaomi Auto: ZCU Architecture Promotes Integration of Intelligent Diagnosis and Other Functions
• Xiaomi Auto: AI-based Intelligent Diagnosis
• 3.1.4 Leapmotor
• Leapmotor: Intelligent Cloud Diagnosis
• Leapmotor: Battery Diagnosis
• 3.1.5 AITO: Features of Intelligent Diagnosis
• 3.1.6 Li Auto
• Li Auto: Intelligent Diagnosis Service
• Li Auto: AI Large Model for Abnormal Noise Localization
• Li Auto: Intelligent Diagnosis Based on Internet of Vehicles Data
• Li Auto: Intelligent Driving System Health Diagnosis Framework
• Li Auto: Mind GPT Empowers Intelligent Diagnosis
• 3.2 Emerging Auto Brands of Traditional OEMs
  • 3.2.1 ZEEKR
• ZEEKR: Features of Intelligent Diagnosis
• ZEEKR: Intelligent Diagnosis Patents
• ZEEKR: AI Diagnosis
• 3.2.2 IM Motors: Features of Intelligent Diagnosis
• 3.2.3 VOYAH
• VOYAH: Architecture-driven Remote Diagnosis
• VOYAH: Intelligent Cloud Testing Technology
• VOYAH: Intelligent Diagnosis Based on Internet of Vehicles Data
• 3.2.4 AVATR
• AVATR: Features of Intelligent Diagnosis
• AVATR: Intelligent Diagnosis Patents
• 3.2.5 LYNK & CO: Features of Remote Diagnosis
• 3.3 Traditional Independent Brands
  • 3.3.1 Changan
• Changan: 5G-based Remote Diagnosis
• Changan: Intelligent Diagnosis Based on Internet of Vehicles Data
• Changan: Intelligent Diagnosis Patents
• 3.3.2 GAC
• GAC: Features of Intelligent Diagnosis
• GAC: Intelligent Diagnosis Patents (2024-2025)
• 3.3.3 Great Wall Motor
• Great Wall Motor: Intelligent Diagnosis Architecture
• Great Wall Motor: Features of Intelligent Diagnosis
• 3.3.4 Chery
• Chery: Features of Intelligent Diagnosis
• Chery: AI Diagnosis
• 3.3.5 BYD
• BYD: Vehicle Models Supporting Remote Diagnosis
• BYD: Cloud Diagnosis Center
• BYD: Remote Monitoring System
• 3.3.6 FAW Group: AI Diagnosis Patents
• 3.4 Joint Venture/Foreign Brands
  • 3.4.1 Tesla
• Tesla: Application Scenarios of Intelligent Diagnosis
• Tesla: Intelligent Diagnosis Service Process
• Tesla: Features of Intelligent Diagnosis
• 3.4.2 BMW
• BMW: Main Content of After-sales Remote Service
• BMW: Features of After-sales Diagnosis System
• BMW: Maintenance Diagnosis Large Model
• 3.4.3 Volkswagen
• Volkswagen: Feature 1 of Intelligent Diagnosis
• Volkswagen: Feature 2 of Intelligent Diagnosis
• 3.4.4 Toyota
• Toyota: Remote Diagnosis
• Toyota: Remote Service
• 3.4.5 SAIC-GM-Wuling
• SAIC-GM-Wuling: Remote Diagnosis Service
• SAIC-GM-Wuling: Remote Diagnosis Patent 1
• SAIC-GM-Wuling: Remote Diagnosis Patent 2
• 3.4.6 Mercedes-Benz
• Mercedes-Benz: Features of Remote Diagnosis
• Mercedes-Benz: Remote Diagnosis Process

4 Intelligent Diagnosis Suppliers

• 4.1 Suppliers in OEM System
  • 4.1.1 ABUP
• Vehicle Diagnosis Product Architecture
• Vehicle Diagnosis Product Matrix
• Intelligent Diagnosis Business 1: Dual-engine Architecture
• Intelligent Diagnosis Business 2: Data Management Products
• Intelligent Diagnosis Business 3: Vehicle Safety and Health Assistant
• Remote Diagnosis Business 4: Product Architecture
• Remote Diagnosis Business 5: Product Functions
• Major Customers of Diagnosis Products
• 4.1.2 Carota
• Profile
• Intelligent Diagnosis Business
• Features of Intelligent Diagnosis Business
• 4.1.3 Excelfore
• Profile
• Intelligent Diagnosis Platform
• Application Scenarios of Intelligent Diagnosis
• Major Customers
• 4.1.4 EXCEEDDATA
• Data-based Intelligent Diagnosis
• Features of Intelligent Diagnosis Functions
• Application Scenarios of Intelligent Diagnosis
• Intelligent Diagnosis Efficiency
• Intelligent Diagnosis Product Architecture
• Customers of Intelligent Diagnosis Service
• 4.1.5 Huawei
• Huawei: Intelligent Diagnosis Products
• Huawei: Diagnosis Security Solutions
• 4.1.6 Jingwei Hirain
• Jingwei Hirain: Intelligent Diagnosis Tools
• Jingwei Hirain: Intelligent Diagnosis Solutions
• 4.1.7 VECTOR
• VECTOR Software Product Series
• VECTOR Hardware Product Series
• VECTOR XiL Verification System
• VECTOR SiL Automotive Application Analysis
• VECTOR vTESTstudio Cooperation in Automotive
• 4.1.8 Cihon Technology
• Cihon Technology: Intelligent Diagnosis Platform
• Cihon Technology: Feature 1 of Intelligent Diagnosis Platform
• Cihon Technology: Feature 2 of Intelligent Diagnosis Platform
• Cihon Technology: Feature 3 of Intelligent Diagnosis Platform
• Cihon Technology: Intelligent Diagnosis Case 1
• Cihon Technology: Intelligent Diagnosis Case 2
• Cihon Technology: Intelligent Diagnosis APP
• 4.1.9 Desay SV
• 4.1.10 Banma Zhixing
• 4.1.11 Beijing Oriental Jicheng
• 4.1.12 Zhongguancun Kejin Technology
• 4.1.13 Carlinx Tech
• 4.2 Suppliers in After-market System
  • 4.2.1 Launch Tech
• Profile
• Remote Diagnosis Equipment
• 4.2.2 Autel
• Profile
• Remote Diagnosis Platform
• 4.2.3 Xtool
• Profile
• Strength
• Product Matrix
• New Energy Vehicle Diagnostic Instruments

5 Summary and Trends of Intelligent Diagnosis Market

• 5.1 Summary of Intelligent Diagnosis Application by OEMs
• Summary of Intelligent Diagnosis Application by OEMs: Internet-based Auto Brands
• Summary of Intelligent Diagnosis Application by OEMs: Emerging Auto Brands of Traditional Brands
• Summary of Intelligent Diagnosis Application by OEMs: Traditional Independent Brands
• Summary of Intelligent Diagnosis Application by OEMs: Joint Venture Brands
• 5.2 Summary of Intelligent Diagnosis Business of Suppliers
• Summary of Intelligent Diagnosis Business of Suppliers (1)
• Summary of Intelligent Diagnosis Business of Suppliers (2)
• Summary of Intelligent Diagnosis Business of Suppliers (3)
• Summary of Intelligent Diagnosis Business of Suppliers (4)
• 5.3 Intelligent Diagnosis Patent Analysis
• Number of Automotive Intelligent Diagnosis Patents
• Ranking of Suppliers by Number of Patents
• Ranking of OEMs by Number of Patents
• 5.4 Development Trends of Automotive Intelligent Diagnosis
• Trend 1
• Trend 2
• Trend 3
• Trend 4