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Electric Vehicle Battery Management Using Edge Computing with Context Analytics

IP.com Disclosure Number: IPCOM000247366D
Publication Date: 2016-Aug-29
Document File: 2 page(s) / 121K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system and method for running an edge analytics rules engine on the vehicle’s gateway in order to manage the life of an electric vehicle (EV) battery.

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Electric Vehicle Battery Management Using Edge Computing with Context Analytics

When outside temperatures drop below zero degrees Celsius (0°C), the driving range of electric vehicles (EVs) is diminished by approximately 25%-50%, depending on the model. Even though most cars have temperature sensors installed to monitor real temperature, predicting the life of the EV battery for an upcoming trip is difficult.

An EV has a gateway, which is a microprocessor attached to the battery of the car

control center.

The novel contribution is a system and method for running an edge analytics rules engine on the vehicle's gateway in order to manage the life of an EV battery.

The edge analytics rules engine runs on the EV and collects data from a few sources:

1. The EV sensors (e.g., real time temperatures of the battery and environmental air temperature, battery metrics, etc.)

2. Cloud databases (e.g., weather) to create context relative to forecasted weather conditions

3. Associated mobile devices (e.g., the driver's calendar, electronic map, etc.), to obtain input about the driving plan

Based on the context of information, including real-time data and context analytics, the system constructs a dynamic threshold of conditions to predict battery life for the next n number of hours over the range of travel. As the EV approaches the threshold, or before the driver begins the next trip, the system alerts the driver to charge battery and to what level to ensure that the battery...