Li Bin, a vice president at Li Auto, announced that the company’s 400,000th car rolled off the assembly line at its factory in the eastern Chinese city of Changzhou on Saturday, June 17, 2023. Credit: Li Auto
Li Auto on June 17 unveiled details of its first purely battery-powered electric vehicle with an expected price tag of around RMB 500,000 ($69,955), claiming its supercharging facilities could give up to 400 kilometers (249 miles) of charge in less than 10 minutes.
The company also announced plans to release an automated driving function that it says will allow commuting drivers to relax their grip in urban traffic later this year, aiming to attract tech-savvy Chinese customers.
Why it matters: Li Auto is catching up with rivals in deploying advanced driver assistance systems (ADAS) at a faster pace than expected, which could be a key differentiator in the driving experience for the company, according to a June 18 note written by Jefferies analysts.
The analysts added that the price range of Li Auto’s first battery EV would be in a “sweet spot” that could ease margin pressure in the future. The Chinese carmaker for now has three extended-range electric sports utility vehicles on sale.
First BEV: Named Mega, Li Auto’s long-anticipated first all-electric is a multi-purpose vehicle with a price range of RMB 500,000 and above, vice president Liu Jie said at a corporate event on June 17.
Capable of traveling 400 km after 9.5 minutes of fast charging, the vehicle is scheduled for release later this year.
Liu also spoke of the company’s goal for the Mega to become the top-selling vehicle in its price segment, regardless of vehicle type.
Li Auto has set an initial goal of delivering 5,000 Mega vans per month, Chinese media outlet Jiemian reported, citing company insiders. By comparison, Geely’s premium EV brand Zeekr in May delivered 2,106 units of its 009 MPVs, priced between RMB 499,000 and RMB 588,000.
Driver assistance software: Li Auto also revealed plans to begin internal testing of its automated driving function for complex urban scenarios, called city NOA (standing for Navigate On Autopilot), with a cohort of selected owners in Beijing and Shanghai later this month.
Vice president Lang Xianpeng said the company’s deep learning model would enable vehicles to perceive their surroundings and make decisions similar to human drivers, as its growing fleet of software users has effectively driven over 600 million kilometers (373 million miles) to date.
Lang added the cars would be able to navigate on fixed routes for daily commuters in big cities with heavy traffic after the initial two to three weeks of training with its collection of datasets. The function will be rolled out to users from 100 major cities by year-end via over-the-air updates.
Some rivals have announced respective plans to compete for users with similar offerings. Xpeng Motors’ XNGP function for urban driving is available to owners in four major cities, while Huawei aims to release its Autonomous Driving Systems to Aito owners in 45 cities this year.
Second plant: The accelerated move to BEVs also comes as Beijing-based Li Auto recently received a green light to open its second plant in the nation’s capital, according to a document (in Chinese) released by the Ministry of Industry and Information Technology on June 16.
The company will build its all-electrics in the RMB 6 billion factory later this year, state-owned media outlet Beijing Daily reported in late 2021. Built on the base of an old plant owned by Korean automaker Hyundai, the facility will have an initial capacity of 100,000 units annually.
Li Auto currently has one factory in operation at a monthly capacity of 30,000 units in the eastern city of Changzhou. Its year-to-date deliveries exceeded 106,542 units as of May and chief executive Li Xiang expected its monthly delivery to reach a milestone of 30,000 units in June.
Jill Shen is Shanghai-based technology reporter. She covers Chinese mobility, autonomous vehicles, and electric cars. Connect with her via e-mail: jill.shen@technode.com or Twitter: @yushan_shen
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