The Xiaomi Pengcheng has torn off its camouflage and is about to launch, so why is it still running on the road? Will testing continue after the official release?
Tearing off the camouflage does not mean the testing is over; it simply means the testing has entered the final fine-tuning and optimization stage before launch. Even after the official release and delivery, our testing will not stop and will continue to iterate throughout the product's entire lifecycle.
Here is a very intuitive example: camouflage stickers and kits on the vehicle's surface will alter the airflow direction and interfere with wind noise test results. Only by completely tearing off the camouflage can we measure the true wind noise performance that is exactly the same as the user's mass-produced vehicle, allowing engineers to make final fine-tuning optimizations based on real sensory experiences.
The core of pre-mass production testing is to verify whether the design meets the standards, while the de-camouflage testing near launch is the final round of full-scenario experience refinement on vehicles in a state closest to mass production. Everything from noise control under different road conditions and air conditioning perception in different climates, to the smoothness of powertrain under full-load long-distance driving, will undergo another round of comprehensive calibration to ensure that the state delivered to users is mature and stable.
After the official launch and delivery, we will also continue to conduct generalized testing. Pre-mass production testing is based on validating known risks, while post-mass production testing proactively explores more long-tail scenarios to capture low-probability potential issues. The road conditions, climate, and usage habits in the real world are infinitely complex. Only by continuously running in real environments can we constantly discover room for optimization and subsequently bring a better experience to users through OTA.
There is no endpoint to quality refinement, and progress in testing is endless. Whether it is over-validation before launch or continuous iteration after launch, the essence is to find potential problems users might encounter in advance, keeping the product's reliability and experience consistently top-notch.