In the world of self-driving technology, the market has come to realize that laser-based sensors — dubbed “LiDAR” — are necessary to give cars the ability to perceive their surroundings. That’s why leading LiDAR makers like Luminar (NASDAQ:LAZR) and Velodyne (NASDAQ:VLDR) have turned into Wall Street’s darlings. But the market’s biggest winner in this space might be neither of those headline names. Rather, it might be a smaller, less-talked-about company by the name of Aeva Technologies (NASDAQ:AEVA). Indeed, according to my numbers, Aeva stock could actually soar more than 10X from its current price.
Why? Because while Luminar, Velodyne, and everyone else is busy making traditional “3D LiDAR,” Aeva is breaking ground on a potentially game-changing new class of “4D LiDAR” sensors.
The fourth dimension is velocity (something that is very important in automotive perception). To be sure, this new LiDAR technology is relatively unproven when stacked up to 3D LiDAR today — but Aeva is starting to prove its technology in a meaningful way, and there’s reason to believe that this company’s 4D LiDARs will be very widely used by 2030.
If so, then the numbers say tiny AEVA stock could soar 10X.
Here’s a deeper look:
AEVA Stock: The Future of LiDAR?
The bull thesis on Aeva Technologies all boils down to one thing: This company is pioneering a potentially game-changing technology in the soon-to-be-enormous LiDAR space.
Here’s the story.
Most LiDAR makers in the world build their sensors on something called Time-of-Flights (or ToF) techniques. ToF LiDAR sensors essentially send out multile laser pulses into their surrounding environments, and measure the time it takes for those pulses to return to the sensor. They use the “time of flight” as a proxy for distance.
While ToF LiDAR sensors are cool, they also provide a choppy signal that is open to ample interference/noise from sunlight photons and other lasers. They also don’t simultaneously capture velocity information, since doing so is impossible with laser pulses.
To address these shortcomings, Aeva is pioneering a new type of LiDAR sensors built on something called Frequency Modulated Continuous Wave (or FMCW) techniques.
Unlike ToF sensors, FMCW sensors transmit and receive a continuous laser beam, and measure differences in the frequencies of the outgoing laser beam from the incoming one to measure the distance of objects. In other words, ToF uses time to measure distance, whereas FMCW uses frequency to measure distance.
The critical difference here is that ToF sends out laser pulses, while FMCW deploys one continuous laser beam. Pulses provide choppy signal subject to noise, and can’t capture velocity information. Continuous beams provide fluid signal with significantly less noise, and can simultaneously capture velocity information (hence the “4D” nickname).
To that end, FMCW LiDAR sensors robustly address the shortcomings of ToF LiDAR — and Aeva is the undisputed leader in FMCW LiDAR technology.
The Luminar of FMCW LiDAR
To be clear, I’m not saying that FMCW tech will make ToF tech obsolete. FMCW sensors also have their own shortcomings, including range, speed and cost – the last of which is the biggest obstacle to adoption today.
As such, in the self-driving world of tomorrow, high-quality ToF LiDAR sensors with smart adjustments for noise cancellation project as the most commonly adopted solution.
But, the innate advantages of FMCW means that there will inevitably emerge a huge market for FMCW LiDAR sensors over the next decade – likely in the premium auto market, where zero interference is a meaningful feature and price is less of an obstacle.
Aeva is at the epicenter of that market.
Indeed, Aeva is simply the “Luminar of FMCW LiDAR sensors”.
That is, when it comes to FMCW sensors, Aeva has:
- The right roots. Aeva was founded by two highly-regarded former Apple (NASDAQ:AAPL) engineers, and now counts semiconductor and auto industry veterans as execs.
- The best technology. Aeva’s proprietary, first-to-market FMCW LiDAR sensors operate 5X faster than legacy LiDAR tech, while drawing on 10X less power, leading to superior performance and durability.
- The strongest partnerships. Aeva’s market-leading technology has been validated by customers, as the company has partnered with 2 top truck programs, 3 global luxury sedan makers (including Porsche and Audi), and 2 top mobility/tech companies.
Net net, Aeva is the best-in-class FMCW LiDAR sensor maker in the world – and a company that projects as a very important player in the premium self-driving car world.
Of course, that has bullish implications for Aeva’s stock.
Aeva Stock Is Undervalued
By my numbers, Aeva’s relatively obscurity has left shares of Aeva dramatically undervalued.
I think it is very likely that, by 2030, Aeva’s FMCW technology is installed in roughly 5% of semi- and fully-autonomous cars globally (mostly premium vehicles). That implies about 3 million cars outfitted with Aeva’s tech. At about two sensors per car and a $1,000 per sensor, that leads to around $6 billion in revenues. EBITDA margins should hover around 45%, based on management projections and the fact that this is a high-margin, low-cost business.
Based on those assumptions, my modeling says Aeva could do about $10 in earnings per share by 2030. A simple 20X multiple on that implies a long-term potential price target here of $200.
The AEVA stock price today hovers around $16.
Thus, this is a potential 10X winner in the making.
The self-driving boom will produce multiple big winners. Aeva has a unique technology advantage in the self-driving technology space. That’s why AEVA stock is one of the best growth stocks to buy today.
But it’s not the best growth stock to buy today.
Instead, the best growth stock to buy today is a company that reminds me of a young Amazon (NASDAQ:AMZN). Indeed, I think buying this stock today could be like buying AMZN stock back in 1997 — before it soared thousands of percent.
Which stock am I talking about?
On the date of publication, Luke Lango did not have (either directly or indirectly) any positions in the securities mentioned in this article.
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