ADAS & Autonomous Vehicle Engineering - April 2023 - 3

The Navigator
Finding EV range through compute efficiency
This past January, I was among tens of thousands
who returned to Las Vegas for CES-the
show's reawakening after the pandemic. Some
definite themes emerged from the dozens of
conversations I had over four days. Particularly
prominent among those was a renewed focus on
computing power efficiency in the vehicle.
We're currently amid multiple transitions in
the auto industry: electrification, more automation,
and the rise of software-defined vehicles. Vehicle
developers are finding that achieving higher levels
of driving automation, within increasing layers of
software, is creating greater energy
demand in EVs.
Creating the software-defined
vehicle and enabling features to
be added via over-the-air updates
requires new electrical/electronic
(E/E) architectures. With these come
a nearly industry-wide adoption of
more centralized compute platforms
with more powerful system-on-achip
(SoC) processors like the Nvidia
Orin and Qualcomm Snapdragon Ride. Centralized
compute is replacing the dozens of low-power
microcontrollers that have been used in vehicles
for decades.
These SoCs offer vastly higher performance.
40 kWh out of the 65kWh available in the Bolt,
leaving the vehicle with a potential maximum range
of about 80 miles (129 km).
Chips like Orin and those used by Cruise and
others are very much general-purpose chips that
are extremely flexible and can be used for broad
range of applications. However, they also have a lot
of capabilities not needed in the automotive space,
resulting in wasted energy.
A new generation of SoCs coming from
Simply adding
more battery
and more
computing
power is not
an acceptable
option.
companies like Qualcomm, Ambarella and Recogni
are more optimized for automotive use cases. Those
focus on the types of processing cores
needed to handle in-vehicle tasks such
as image processing for driver assist.
In live demonstrations during CES,
both Ambarella and Recogni showed
their chips processing automotive
data side by side with Orin systems
and providing higher throughput at
a fraction of the power consumption.
Cruise is also developing its own optimized
processors that will reduce
power consumption by over 75% for next-generation
vehicles, the company claims.
With new generation vehicles entering the
For example, Chinese EV startup Nio has a compute
platform in its ET7 sedan dubbed Adam which uses
four Orins for a combined 1,000 trillion operations
per second (TOPS). This can run advanced automated
driving capabilities and a variety of other
functions. However, it also consumes over 800W of
power-which is why such systems are only used on
electrified vehicles. Traditional 12V internal combustion
electrical systems max out at about 2.5kW of
electrical power making such a system unfeasible.
A more extreme example comes from GM's
automated driving subsidiary Cruise, where the
current compute platform in its Chevrolet Boltbased
robotaxi eats up to 4kW. Over a 10-hour
shift, the compute in that robotaxi would gobble
market with higher resolution cameras that jump
from 1.2MP to as much as 8MP, and imaging radar
and lidar, the amount of data that needs to be
processed in real-time is exploding. Meanwhile
there is a push for more affordable EVs with
longer ranges.
Simply adding more battery and more
computing horsepower is not an acceptable option.
Electric propulsion is already quite efficient, but
every aspect of the vehicle must become thriftier
with its use of electrons if all the competing goals
are expected to be achieved.
Compute power in the vehicle becomes more
important by the day. But it can't consume all the
energy needed for propulsion and climate control
at an unlimited cost if the industry is to eventually
replace all IC-engine vehicles. ■
Sam Abuelsamid
Principal Analyst,
eMobility
Guidehouse Insights
sam.abuelsamid@
guidehouse.com
ADAS & AUTONOMOUS VEHICLE ENGINEERING
April 2023 3
ADAS & Autonomous Vehicle Engineering - April 2023

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