Method and system for predicting vehicle battery health using a collaborative vehicle battery health model
First Claim
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1. A method for predicting replacement time of a vehicle battery comprising:
- providing a processor configured to;
collect battery performance data from a plurality of vehicles though a wireless receiver;
identify the battery performance data associated with vehicles belonging to a peer group defined by a mutual year of manufacture;
apply a statistical operation to the battery performance data so as to calculate an adjustment parameter reflecting the mutual year of manufacture;
use a collaborative health model incorporating the adjustment factor to predict a replacement date of a battery of a vehicle associated with the peer group, the collaborative health model implemented as
Cdeg(t)=CNe−
cz(1-Zw(t)/1.6ZIEC),wherein Cdeg(t) is time dependent, battery capacity, CN is nominal battery capacity, Zw(t) is time dependent, weighted throughput, ZIEC is a standard throughput value, and cz is the adjustable parameter.
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Abstract
A method includes collecting vehicle health data from a plurality of vehicles. A peer group is identified among the plurality of vehicles. The collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.
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Citations
14 Claims
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1. A method for predicting replacement time of a vehicle battery comprising:
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providing a processor configured to; collect battery performance data from a plurality of vehicles though a wireless receiver; identify the battery performance data associated with vehicles belonging to a peer group defined by a mutual year of manufacture; apply a statistical operation to the battery performance data so as to calculate an adjustment parameter reflecting the mutual year of manufacture; use a collaborative health model incorporating the adjustment factor to predict a replacement date of a battery of a vehicle associated with the peer group, the collaborative health model implemented as
Cdeg(t)=CNe−
cz (1-Zw (t)/1.6ZIEC ),wherein Cdeg(t) is time dependent, battery capacity, CN is nominal battery capacity, Zw(t) is time dependent, weighted throughput, ZIEC is a standard throughput value, and cz is the adjustable parameter. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for predicting a replacement time of a vehicle battery, the system comprising:
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a processor in communication with a wireless network, the processor configured to; collect battery performance data from a plurality of vehicles though a wireless receiver; identify the battery performance data associated with vehicles belonging to a peer group defined by a mutual year of manufacture; apply a statistical operation to the battery performance data so as to calculate an adjustment parameter reflective of the mutual year of manufacture; use a collaborative health model incorporating the adjustment factor to predict a replacement date of a battery of a vehicle associated with the peer group, the collaborative health model implemented as Cdeg (t)=CNe−
cz (1-Zw (t)/1.6ZIEC ),wherein Cdeg(t) is time dependent, battery capacity, CN is nominal battery capacity, Zw(t)is time dependent, weighted throughput, ZIEC is a standard throughput value, and cz is the adjustable parameter. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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Specification