Three Types Of Technologies Enabling Intelligent Electric Vehicles

Three Types Of Technologies Enabling Intelligent Electric Vehicles

In my last article, I discussed monetization opportunities of the intelligent electric vehicle (IEV) industry. In this article, I will examine the enabling technologies for intelligent electric vehicles to realize these monetization opportunities. My general observation is that the IEV industry is evolving through three stages of development: electrification, intelligence and ecosystem.

Electrification is the process of powering the vehicle by electricity, and the core objectives of electrification is to maximize travel range per charge, charging speed and charging convenience. Upon the foundation of electrification, intelligence—such as smart cockpit and autonomous driving—can be infused into IEVs to make the driving and riding experiences more convenient and enjoyable. With sufficient compute capability, an application ecosystem can be developed for IEVs, similar to how mobile applications have evolved on smart phones. With an IEV ecosystem developed, many usage scenarios beyond mobility will emerge.

Indeed, the development of Tesla has been following this exact path. In the early years of Tesla, electrification was the key technical focus. At the time, Tesla replied on external supply chain—e.g., MobilEye—to deliver intelligence solutions. Then as Tesla gained more market share and as their battery technologies gradually matured, Tesla shifted their R&D focus to intelligence, especially autonomous driving technologies. I expect that Tesla will shift their focus to the ecosystem as they deploy more standard compute platforms and gain higher market shares in the future.

With this development trend in mind, let us review several IEV-enabling technologies.



Existing EV batteries contain liquid electrolytes, while semi-solid state—or even solid-state batteries—would deliver a much higher energy density per unit area due to their compact size, and solid-state battery technologies are under active development.

In advancement of this trend, CATL announced the release of Qilin battery, which enables range of 1,000 kilometers on one charge. Semi-solid and solid-state batteries could further extend this range and eliminate the range anxiety of EV users.


Battery packaging technologies are essential for the space utilization, reliability and safety of IEVs. Cell to pack (CTP) technology, mainly developed by CATL, directly integrates battery cells into battery pack to optimize space utilization and energy density.

Improved upon CTP, cell to body (CTB) technology, developed by BYD, integrates battery back into vehicle body floor panel to further optimize vehicular space utilization. Cell to chassis (CTC), developed by Tesla, is the process of directly integrating the battery cells into the vehicle chassis. This way, batteries can be tightly integrated with EV power system. Tesla projected a 55% cost reduction and a 35% space reduction with CTC technology.

Fast Charging

One solution to eliminating range anxiety of IEV users is fast charging. The main technical constraint for fast charging is high-power-charging infrastructure. The deployments of high-power-charging infrastructure require an upgrade of the power grid and usually demand support from different governments.

China, for example, has invested heavily on its charging infrastructure projects, installing a large amount of high-power-charging stations along its highways, effectively boosting IEV penetration rate in China.


Autonomous Driving

LiDAR-based autonomous driving solutions have been the mainstream since the inception of autonomous driving. In recent years, Tesla has demonstrated the feasibility of vision-based autonomous driving. Specifically, Tesla has utilized transformer network architecture to achieve high perception accuracy. Many companies will likely follow suit to invest in transformer architectures.

However, the success of Tesla has been based on the enormous amount of data available to refine their system, instead of the network architecture. Hence, the key competition point of autonomous driving technologies lies in data collection and data infrastructure of each original equipment manufacturer (OEM).

Electrical/Electronic (E/E) Architecture

E/E architecture refers to the convergence of electronics and network components into one integrated system to satisfy the needs of an ever-increasing number of vehicle functions. A recent technical trend is centralized E/E architecture, which brings several technical advantages, including hardware/software separation, more efficient computing resource utilization through virtualization, high-speed data exchange, extensible and flexible sensor and actuator interfaces. Tesla has been the first OEM to deliver centralized E/E architecture, and Nvidia’s recently released Thor compute system is another example of centralized computer for vehicles.


Augmented Reality (AR)

AR technologies can potentially enable many in-vehicle applications. AR, for example, can greatly enhance safety through augmenting navigation, cruise control and lane departure warning.

Also, by combining AR and vehicle-to-everything (V2X) technologies, drivers can instantly obtain nearby vehicle information through AR to further improve safety. In addition, for passengers in car, AR technologies can transform the in-cabin space into an entertainment room, in which passengers can enjoy immersive games or shows.


The U.S. is a nation on wheels, as Americans spend over 70 billion hours driving per year, and each driver spends on average 52 minutes driving per day. Because of the spacious environment, the amount of time drivers and riders spend in cars, and the health technologies that can be integrated in cars, IEVs are intriguing platforms to efficiently and effectively monitor drivers and riders’ health conditions, based on which health professionals can deliver health advice. The technical challenges for this scenario include reliable sensing, health AI capabilities and connectivity, among others.


In summary, the IEV industry shows enormous potential, and companies in the industry are competing fiercely on ensuring the safety of their technical supply chains. For instance, China’s BYD has been actively acquiring lithium mines globally to guarantee that they have sufficient raw materials for electrification. Tesla has invested heavily on computing technologies and refuses to rely on external suppliers on intelligence. Many similar cases can be found in many IEV OEMs.

I expect the IEV OEMs’ continuous investments to develop independent supply chains will continue in the next few years, and many startups in the IEV supply chain will benefit. For startups in the IEV OEM space, it will become increasingly difficult to compete in the electrification and intelligence areas, but many opportunities will emerge in the ecosystem space. Therefore, it could be a smart move for IEV OEM startups to focus on a few deep use cases, such as in-vehicle healthcare.

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