Predictions-based battery-saving
for preheating and precooling in
hybrid vehicles
Hybrid EVs can offer consumers innovative use-cases that a pure
combustion
vehicle can’t. One of these highly rated use cases is preheating/precooling before
departure.
The challenge is to maintain enough battery capacity on arrival to support remote preheating the
next
day.
Predictive services in vehicles, based on driver data, are a fast-developing area of interest
for
OEMs.
CloudMade’s adaptive framework makes predictions that enable many elements of the
driver
experience to be improved. For hybrid vehicles, it is possible to use destination, departure
time and
weather predictions to calculate if there will be enough battery capacity to initiate
preconditioning
when needed on future journeys, and suggest the use of the combustion engine to
ensure this. This new
hybrid vehicle battery management solution can enable greater use of
preconditioning, bringing a
multitude of benefits.
Learn more about this exciting new hybrid vehicle use-case in the video below:
This use-case brings multiple values for both OEMs and end users:
Value for the OEM
- Increased capability of the preconditioning use case increases brand satisfaction
- Monetization opportunities from upselling AI-powered features
- Marketing opportunity for eco benefits
Value for the end user
- Preconditioning is always available before the trip start
- Reduce annoyance / increase satisfaction
- Increased engagement with OEM’s mobile phone companion app
- Improved engine lifecycle from avoiding cold starts
- Reduction of CO2 emissions by reduction of time to warm engine up
CloudMade has all the necessary building blocks to enable the use-case
-
- Predictive departure time
- Predictive route & destination
- Reinforcement learning based on user response