Reshaping of automotive industry pattern under the wave of electrification and intelligence

doi:10.3969/j.issn.1674-8484.2023.06.001

Abstract

Abstract:

The global automotive industry is experiencing a wave of electrification and intelligence. The automotive product definition and industrial pattern are being reshaped. China’s new energy vehicle sales reached 8.3 million units from January to November 2023, a year-on-year increase of 37%, and the penetration rate of new energy vehicles reached 31%. Tesla leads the technological transformation and evolution trend of the global automotive industry. In 2022, Tesla sold 1.31 million vehicles, which is still far behind Toyota (about 10.48 million vehicles) and other manufacturers. However, its market value has exceeded US$700 billion, ranking first among global automakers, reflecting investors' optimism about its long-term development. Reviewing Tesla's development history, the author concludes that its success is mainly based on three reasons: self-developed full-stack technology; defining products based on first principle; and continuous cost reduction driving sales growth. New entrants and technology companies are actively following up, and traditional companies are accelerating their transformation. In 2022, local brands already accounted for 80% of China's new energy vehicle market. In the future, the penetration rate of new energy vehicles in China and the world will continue to increase. Under the wave of electrification and intelligence, the pattern of the automotive industry will continue to change. Companies with full-stack self-developed capabilities, product definition and reconstruction capabilities, and industry chain coordination capabilities are expected to gain higher market share.

Key words: new energy vehicle, Tesla, intelligence, independent brand, overseas market

CLC Number:

U469.7

XU Yingbo, LI Jingtao, GAO Feixiang, WU Pingyue, LI Zheng. Reshaping of automotive industry pattern under the wave of electrification and intelligence[J]. Journal of Automotive Safety and Energy, 2023, 14(6): 651-663.

Figures/Tables 18

References 35

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代码	公司	市值亿美元	收入预测亿美元	利润预测亿美元	市销率PS	市盈率PE
TSLA.O	特斯拉	7 112	971	80	7.3	88.5
1211.HK	比亚迪	940	834	43	1.1	22.1
LI.O	理想	404	166	11	2.4	37.6
NIO.N	蔚来	124	88	-20	1.4	—
XPEV.N	小鹏	140	50	-16	2.8	—
TM.N	丰田	3 054	2 845	245	1.1	12.5
VOW.DF	大众	369	3 265	167	0.1	2.2
F.N	福特	393	1 638	66	0.2	6.0
GM.N	通用	368	1 699	98	0.2	3.7

代码	公司	市值亿美元	收入预测亿美元	利润预测亿美元	市销率PS	市盈率PE
TSLA.O	特斯拉	7 112	971	80	7.3	88.5
1211.HK	比亚迪	940	834	43	1.1	22.1
LI.O	理想	404	166	11	2.4	37.6
NIO.N	蔚来	124	88	-20	1.4	—
XPEV.N	小鹏	140	50	-16	2.8	—
TM.N	丰田	3 054	2 845	245	1.1	12.5
VOW.DF	大众	369	3 265	167	0.1	2.2
F.N	福特	393	1 638	66	0.2	6.0
GM.N	通用	368	1 699	98	0.2	3.7

	计算硬件		AI软件
	训练计算机	自动驾驶计算机	神经网络	数据标注	模拟
传统车企	外包	外包	垂直整合	外包	外包
Waymo	垂直整合	垂直整合	垂直整合	垂直整合	垂直整合
Tesla 2018	外包	外包	垂直整合	外包	—
Tesla 2021	垂直整合	垂直整合	垂直整合	垂直整合	垂直整合

	计算硬件		AI软件
	训练计算机	自动驾驶计算机	神经网络	数据标注	模拟
传统车企	外包	外包	垂直整合	外包	外包
Waymo	垂直整合	垂直整合	垂直整合	垂直整合	垂直整合
Tesla 2018	外包	外包	垂直整合	外包	—
Tesla 2021	垂直整合	垂直整合	垂直整合	垂直整合	垂直整合

类型	质量能量密度 (Wh·kg^-1)	体积能量密度 (Wh·L^-1)
普通LFP电池包	80~100	180~230
NCM523电池包	110~150	250~380
NCM811电池包	170~180	410~440
比亚迪刀片电池包	140~150	439~450
宁德时代CTP NCM电池包	≥ 250	≥450
宁德时代CTP LPF电池包	≥160	≥ 290