Proceedings of the 2021 5th CAA International Conference on Vehicular Control
and Intelligence (CVCI), Tianjin, China, October 29-31, 2021
An Overview of the Zoox Smart Automatic Thermal Control Design
-- An Autonomous Electric Taxi*
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) | 978-1-6654-0847-9/21/$31.00 ©2021 IEEE | DOI: 10.1109/CVCI54083.2021.9661241
Qinling Zheng and Paul Mueller
Abstract— Proper thermal system control design can lead to
enhanced vehicle battery economy, range, reliability, longevity,
passenger comfort, and safety in an electric vehicle;
advancements in thermal control design remain key as “new
technologies, consumer demand, societal concerns, and
government regulations emerge and evolve” [1]. This paper is an
overview of the thermal control design used by autonomous,
electric robotaxi start-up company -- Zoox. Different than many
other traditional vehicle thermal control designs, the entire
thermal system in the Zoox design features intelligence,
robustness, energy efficiency, safety, and high performance to
meet Zoox’s spirit of a rider focused taxi. Discussion of the
challenges and solutions together with the high-level control
design strategies are presented in the paper.
each bench seat. The vehicle is designed with a tall roof and
low floor providing comfort for taller riders and making it
easier to enter and exit through the side doors.
I. INTRODUCTION
Zoox has been focusing on creating an entirely new
autonomous, electric vehicle targeting the robotaxi market [2].
The company's approach is centered around the fact that a
retrofitted vehicle is not optimized for autonomy. Zoox has
applied the latest techniques in automotive, robotics, and
renewable energy to build a symmetrical, bi-directional,
battery-electric vehicle to solve the unique challenges of
autonomous mobility [3-4]. Founded in 2014, the company
built its first prototype in 2015, first demonstrated SAE Level3 autonomy in 2017, began durability testing of production
prototypes in 2019, and established a production line in
Fremont, California in 2020. The company’s name, Zoox, is
short for zooxanthellae -- a mobile, algae-like organism
powered by photosynthesis that thrives in mutually beneficial
relationships with coral.
To achieve the goal of making personal transportation
safer, cleaner, and more enjoyable for everyone, the whole
team at Zoox has created an entirely new form of
transportation. Zoox will provide mobility-as-a-service in
dense urban environments. Zoox will handle the driving,
charging, maintenance, and upgrades for its fleet of vehicles,
offering an effortless and enjoyable travel experience for its
passengers.
To differentiate itself from other existing autonomous
vehicle designs, Zoox has spent the last few years working on
outfitting its autonomous vehicle with the ability to drive both
forward and backward, or “bi-directionally.” Zoox’s vehicle
has also been designed to operate at speeds up to 75 mph. Fourwheel steering gives the robotaxi a tight turning radius of 28.2
feet making simple work of some U-turns and parking spaces
that require other vehicles to use their reverse gear.
Figure 1. Zoox Autonomous Robotaxi First Look [5]
Artificial intelligence helps identify all objects perceived
by the sensor suite, which when combined with GPS data and
detailed map information provide the Zoox vehicle with the
information it needs to determine a route and formulate
specific routing around obstacles, congestion, construction,
etc. Like most early autonomous vehicles, Zoox’s robotaxi is
decked out in safety technology. There’s a crown of six
rotating LIDAR pucks on the roof, each providing an
overlapping 270-degree field of view that when combined with
a full suite of radar and camera gear provides 360-degree
awareness up to 150 meters in all directions virtually
eliminating blind spots as well as providing redundancy in the
event that a sensor fails.
The interior design of Zoox’s vehicle is neutral and
passenger friendly, materials used are premium as indicated by
Figure 2. The cozy bench seats, which face inward (hence the
term “carriage-style”) are surrounded by what looks like
textured fabric. The seats also conceal what Zoox proposes is
a radical rethink of how airbags work. There are cupholders
and wireless charging mats between seats. And the ceiling has
a starry sky pattern, the kind commonly seen in luxury
vehicles. A small touchscreen at each seat is the most obvious
tech found inside which can allow passengers to control music,
radio, air conditioning, or see their route and estimated time of
arrival.
By designing the vehicle with inward facing bench seats,
Zoox is able to provide a considerable amount of personal
space for each passenger as shown in Figure 1. In addition, this
allows the batteries and drivetrains to fit entirely underneath
*Research supported by Zoox Inc.
Q. Zheng is with the Zoox Inc. Foster City, CA 94404 USA (e-mail:
jzheng@zoox.com).
P. Mueller is with the Zoox Inc. Foster City, CA 94404 USA (e-mail:
paulmueller@zoox.com).
978-1-6654-0847-9/21/$31.00 ©2021 IEEE
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cannot be decoupled into smaller subsystems to enable singleinput-single-output (SISO) control system design.
Figure 2. Zoox Interial Design [5]
The front and rear battery packs combined store an
impressive 133 kWh of energy, which is a little bigger than the
packs that currently power Tesla’s most capable vehicles.
These battery packs will last for 16 hours of continuous use
and allow the robotaxi to be be recharged overnight and spend
two-thirds of its day in use.
Currently, Zoox is focused on testing on private and public
roads as the company moves towards launching the first Zoox
ride-hailing service. Since the vehicle is being designed for
ride-hailing in urban environments, most of the fleet is testing
in three cities: Las Vegas, Nevada; Foster City, California; and
San Francisco, California. The company plans to launch an
app-based ridesharing service. Its first target markets will be
San Francisco and Las Vegas.
After this brief review of the Zoox vehicle, one can imagine
that such a rider focused fully autonomous robotaxi concept
poses a great challenge with thermal control design. This paper
will review the existing and some on-going thermal control
designs in the Zoox vehicle. Control design challenges and a
high-level design overlook will be presented in the following
section.
II. THERMAL CONTROL
Thermal control in the Zoox vehicle is currently focused
on, but not limited to, heating, ventilation, air conditioning
(HVAC) control, and cabin climate control. HVAC control
involves coolant loop and refrigerant loop control, while cabin
climate control targets the regulation of the air loop in the
cabin. When compared with traditional vehicle thermal design,
the artificial intelligence and electric vehicle components (e.g.,
super-computing/memory components, high-voltage batteries,
electric motors, related converters and inverters) need to be
considered, since the Zoox robotaxi is an autonomous vehicle
as well as an electric vehicle. It is a very complicated multiinput-multi-output (MIMO) system, with very tight inter-loop
dynamic coupling among all three loops as shown in Figure 3.
There are about one hundred sensors (such as temperature
sensors, pressure sensors, valve position sensors, flowrate
sensors) in the HVAC system and the coolant loop. There are
more than a hundred input and outputs (I/Os) in the cabin
climate control loop such as temperature sensors, air flowrate
sensors, relative humidity sensors, air quality sensors (AQS),
smoke detectors, solar radiation sensors, speed sensors, and
vent positions sensors.
Another characteristic in each loop is that there are multiple
actuators for control input and multiple targets to be regulated
as planned output. Furthermore, the input and output are not
balanced, as they do not have 1-to-1 relationship, and therefore
Figure 3. Inter-loops coupled dynamics
Let’s take a close look at each loop. In the coolant loop, the
control input consists of the radiator fan speed, multiple pump
speeds, flow rate valve position, and a coolant route valve
position. The targets to be regulated include the temperatures
of all critical components, such as the motor, battery, GPU and
CPU, to ensure they can operate at a healthy level without
degrading performance. Meanwhile, the coolant loop is
coupled with a refrigerant loop via a liquid cooled condenser
and chiller. In the refrigerant loop, the input to the plant
includes the compressor speed, condenser speed, evaporator
speed, reheat door position, and purge door position. Outputs
of the HVAC module include the HVAC discharge
temperature, airflow, refrigerant pressure, and temperature.
The air passes through the ventilation duct to the cabin to
regulate the cabin comfort level. Airflow out of the duct and
the air temperature leaving the duct are the main inputs to the
air-loop in the cabin. In the cabin climate control loop, the
temperature levels, airflow rate, and relative humidity level
from passenger prospect of view must be considered when
regulating the targets. The environment air quality inside the
cabin such as smoke level, CO2 level, NO level, etc. should
also be considered. One may also have noticed in Figure 3,
there is also a trade-off between components and cabin
cooling/heating capacity when the total heat/cool capacity is
limited in certain ambient temperature cases. Therefore,
optimized solutions are required to maximize the performance
of the entire thermal system.
Another challenge posed to thermal control engineers is
that much of the dynamics in these three loops are
characterized with nonlinearities and time delay which greatly
decrease the stability margin especially phase margin. This is
the main limitation to applying higher controller bandwidth,
limiting the transient response time. Therefore, a significant
number of lookup tables, which need to be carefully calibrated,
are used to offer a fast pre-act action to compensate for phase
lag.
Robustness requirements are always important in vehicle
control design. Thermal control is also required to be able to
handle cases such as various weather conditions, different
travel speeds, and different computing stress levels. Massive
amounts of simulation tests, vehicle level validations, issue
identifications, design improvement, as well as simulated and
vehicle level shakedown tests have been completed and will
continue as Zoox moves forward.
The highest priority in vehicle design is safety and the same
has been applied to the thermal system design. The Zoox
thermal system is equipped with high accuracy AQS, allowing
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the vehicle to switch the air mode from fresh to recirculation
mode whenever it detects a dangerous level of NO, NO2, CO,
CxHy which might threaten passenger health. A smoke detector
monitors smoke level in the vehicle to ensure the cabin
environment is always comfortable, healthy, and friendly to
children. Highly efficient cabin air filters were selected and
installed in the HVAC modules which can effectively absorb
odors and gases, remove small particles, fungal spores,
bacteria, and even neutralize allergens. Equipped with
hundreds of sensors and I/Os in the vehicle thermal system,
any single sensor fault or an inefficiency of I/O communication
will cause system to shut down, affecting the performance or
functionality of critical components such as motors, inverters,
batteries, or AI related computational equipment. A welldefined fault handling mechanism is developed by the Zoox
thermal system team to ensure that passenger safety has the
highest priority while simultaneously considering comfortable
level.
The current thermal control design ensures that these
control design challenges have all been taken into
consideration. The next mission is to achieve better power
consumption, lower noise vibration performance where better
component design and optimized control will be applied.
Comfort is always a top concern and the Zoox thermal control
team hopes to offer the best travel experience for all
passengers.
As an autonomous robotaxi, bringing intelligence to the
vehicle design will be reflected in every single system in
Zoox’s taxi, including the thermal system. In the following
section, some important smart characteristics in the thermal
system design will be introduced.
III. SMART AUTOMATIC THERMAL CONTROL
The Zoox thermal design adopts an advanced control
design, adaptive estimator/predictor, together while using a
combination of modern machine learning (ML) techniques
making the thermal system smart. Out of the many cuttingedge designs in Zoox’s thermal system, this paper will
introduce a smart power budget design, a smart cabin
temperature estimator, and a smart cabin climate target
recommendation system.
ambient temperature. An air forecast is used to predict
environmental air quality. Supplied with this information, the
ML model will offer a thermal system power budget used by
the cabin climate control, coolant loop control, and refrigerant
loop control.
Figure 4. Smart thermal power budget
B. Smart cabin climate estimator
The thermal system is complicated and widely emerged in
the whole vehicle system and almost covers every dimension
of the vehicle attribute design. Therefore, thermal engineers at
Zoox are working hard to minimize the usage of sensors to
ensure a sleek inertia design, while offering a conformable
cabin climate environment to all passengers. Decoupled zonebased climate control powers the micro-climate control in the
Zoox robotaxi allowing each occupant to have their own
personal comfort level of temperature and airflow. Adaptive
state space observers capture the thermal dynamics caused by
HVAC actuators, solar impact, vehicle speed, door open
condition, and even RH level, and are built to provide breath
level, chest level, and foot level temperature and air-flow rate
for each quadrant as shown in Figure 5 and Figure 6.
A. Smart power budget for thermal system
The smart power budget system uses a time-series ML
approach to predict the most likely amount of power
consumption even before the trip begins, which will be very
informative for trip planning and battery management. The
model development and application schematic are described in
Figure 4.
To have a better prediction result, information such as day
of year and time of day are used to represent the season,
weather, and solar impact. These will be collected as training
features of the ML model. Traffic information collected from
a smart map and distance for suburb/urban environments are
also considered to reflect the thermal cost for different vehicle
velocity levels. A large amount of data will be collected to
prepare our model for high accuracy and with high generality.
In the application stage, after the model is trained and
validated, the main inputs to the model will include several
features. A map and GPS are used to provide vehicle speed
estimation, travel distance, and compute stress level
prediction. A weather forecast estimates solar impact and
Figure 5. Offline observer fitting
Figure 5 shows the how the adaptive state observer is fitted
with collected test data. Figure 6 shows how the observer
provides the estimated information that cannot be measured
directly in the cabin to the cabin climate controllers.
Temperature and airflow are estimated online and adaptively
to minimize the feedback signals’ phase delay. Furthermore,
this type of design allows the controllers to pre-act on typical
process systems with large time-delay and ensure accurate
control.
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Figure 6. Online observer estimating
C. Smart Temperature and Airflow Target Settings
Another smart feature is to offer smart cabin climate control
target via ML and an online training approach such as
incremental reinforcement learning. As shown in Figure 7, the
pre-trained recommended ML model is fed with available
public information such as weather condition, air quality, and
vehicle speed over the course of the trip to offer a
recommended target temperature and comfort air vent
position as an initial target value for the cabin climate control.
Since Zoox will serve passengers as a taxi and may use a
mobile application for initiating service, passenger
information such as age and gender can be used as input to the
ML model to adjust the target preferences. If a passenger has
taken a Zoox taxi before, his/her previous preferences can be
considered by the recommendation system. Otherwise,
whenever a passenger is increasing/decreasing the cabin
climate target setting via the touch screen panel, signals for
reward/punish will be sent to the recommendation system
based on its decision. Combining the offline and online ML
training strategy is adopted to minimize the memory usage
and computation power to allow the recommendation system
to automatically adjust itself to be more personal while
achieving a rider focused, effortless cabin comfort control
goal.
part of the entire vehicle system, its complexity and
importance are motivations to design it right and design it
well. The thermal control team enhanced modern control
design with machine learning and an adaptive scheme to make
it truly intelligent and allow the system to become smarter via
online learning and self-adaptation. Some of the strategies
have been developed, implemented, and are currently in
validating and improving performance stages. There is still
plenty of room for further improvements to performance to
make the product even better. The whole Zoox team will try
its best to deliver a comfortable and safe robotaxi to take you
along your next journey.
ACKNOWLEDGMENT
This research is supported and funded by Zoox, Inc. We
would like to thank the engineers from the
Aero/Thermal/SCM integration team and the thermal system
team in Zoox who provided insight and expertise greatly
assisting the research.
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Ohnsman, Alan. "Robotaxi Startup Zoox Becomes A Big Acquirer Of
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https://zoox.com/
Figure 7. Smart temperature and airflow target prediction
IV. CONCLUSION
As the autonomous driving field becomes more and more
prosperous, it also attracts interest from the fields of research
and industry. Zoox, a young autonomous start-up company is
dedicated to developing a rider-focused electric robotaxi.
Given the many challenges on the road of exploring, the
engineering teams never give up the attempt to offer Zoox’s
future riders the most comfortable and safest experience while
traveling in Zoox’s taxi. Although the thermal system is only
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