Intelligent Control System for Electric Vehicles and Human Powered Vehicles: Technological Evolution from Connected Vehicles to Autonomous Driving

Keywords: electric vehicles, human powered vehicles, intelligent control, connected vehicles, autonomous driving, sensors

abstract

Intelligent control is the development direction of electric vehicles and human powered vehicles. This article analyzes the technical architecture and engineering practice of communication protocols, sensor technology, and autonomous driving.

4.1 Limitations of Traditional Control Systems

Mechanical instrument panel:

Only displaying vehicle speed and battery level, unable to monitor faults in real-time (such as motor overheating and battery abnormalities).

Manual meter:

Relying on manual operation, prone to errors and unable to integrate payment functions (such as traditional Indian Tuk Tuk models).

4.2 Intelligent Hardware Architecture

Main control chip:

Adopting NXP i.MX 8M Plus (quad core A53+NPU, computing power 2.3 TOPS), supporting 4G/5G communication and multi-sensor fusion.

Sensor configuration:

The camera (1080P, FOV 120 °) is used for lane keeping, the millimeter wave radar (77GHz) is used for obstacle detection, and the IMU (six axis) is used for attitude estimation.

4.3 Vehicle networking function

Remote monitoring:

Upload the vehicle status (such as battery voltage and motor temperature) to the cloud platform through the 4G module, with a fault warning accuracy rate of over 95% (such as the Bounce model in India).

Intelligent pricing:

Integrate GPS and high-precision maps, automatically calculate mileage and time costs, support electronic payments (such as GrabPay integration rate>90%).

4.4 Autonomous driving technology

L2 level assisted driving:

To achieve adaptive cruise control (ACC, speed range 0-30km/h) and lane centering (LKA, offset<0.5m), V2X communication is required (such as the Singapore ComfortDelGro test model).

Automatic parking:

Based on ultrasonic radar (detection distance of 5m) and surround view camera, parking time is less than 90 seconds (suitable for narrow street scenes).

4.5 Network Security Protection

Data encryption:

Encrypt communication data using the national security SM4 algorithm to prevent location information leakage (as required by Chinese automotive companies).

OTA upgrade:

Realize seamless upgrade through A/B partition design, upgrade package volume<200MB, upgrade success rate>99% (such as Tesla OTA strategy).

conclusion

Intelligent control needs to shift from "single function" to "systematic interconnection". Through the Internet of Vehicles, autonomous driving, and network security technologies, an efficient and secure travel ecosystem can be built.