Electric vehicle battery monitoring system
First Claim
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1. A battery powered apparatus comprising:
- a battery comprising one or more electrochemical cells, the battery having an output voltage and an output current when delivering power;
a load driven by power delivered from the battery;
a battery output current sensing circuit; and
a battery management system comprising processing circuitry coupled to the battery output current sensing circuit, the processing circuitry configured to model a predicted output voltage of the battery with a battery model neural network comprising;
a first recurrent neural network comprising a first input layer, a first hidden layer, and a first output layer, wherein a node of the first output layer generates a predicted temperature of the battery, anda second neural network comprising a second input layer, a second hidden layer, and a second output layer, wherein the second input layer includes a node that receives the predicted temperature from the node of the first output layer of the first recurrent neural network, and wherein the second output layer includes a node that generates the predicted output voltage of the battery,wherein a particular node of the first hidden layer receives a first input from a node of the first input layer and a second input from a previous time state of the first hidden layer, and wherein a particular node of the second hidden layer receives a first input from a node of the second input layer and a second input from a previous time state of the second hidden layer.
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Abstract
Systems and methods for monitoring and controlling a battery are disclosed. Systems can include a battery having an output voltage and an output current when delivering power, a load driven by power delivered from the battery, battery output voltage and current sensing circuits, and processing circuitry coupled to the battery output voltage and current sensing circuits. The processing circuitry may implement a recurrent neural network for battery state estimation.
21 Citations
20 Claims
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1. A battery powered apparatus comprising:
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a battery comprising one or more electrochemical cells, the battery having an output voltage and an output current when delivering power; a load driven by power delivered from the battery; a battery output current sensing circuit; and a battery management system comprising processing circuitry coupled to the battery output current sensing circuit, the processing circuitry configured to model a predicted output voltage of the battery with a battery model neural network comprising; a first recurrent neural network comprising a first input layer, a first hidden layer, and a first output layer, wherein a node of the first output layer generates a predicted temperature of the battery, and a second neural network comprising a second input layer, a second hidden layer, and a second output layer, wherein the second input layer includes a node that receives the predicted temperature from the node of the first output layer of the first recurrent neural network, and wherein the second output layer includes a node that generates the predicted output voltage of the battery, wherein a particular node of the first hidden layer receives a first input from a node of the first input layer and a second input from a previous time state of the first hidden layer, and wherein a particular node of the second hidden layer receives a first input from a node of the second input layer and a second input from a previous time state of the second hidden layer. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A method of operating a battery powered apparatus, the method comprising:
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driving a load of the apparatus with a battery; sensing the output current of the battery at defined intervals while driving the load; predicting an output voltage that will be exhibited by the battery under selected output current conditions using at least first and second recurrent neural networks each comprising an input layer, a hidden layer, and an output layer, wherein a particular node of the hidden layer receives a first input from a node of the input layer node and a second input from a previous time state of the hidden layer; using the first recurrent neural network to generate a predicted temperature of the battery; providing at least the predicted temperature as an input to the second neural network, wherein the second neural network generates the predicted output voltage; and driving the load of the apparatus with the selected current sourced from the battery. - View Dependent Claims (8, 9)
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10. An electric vehicle with a battery monitoring system, the vehicle comprising:
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a battery; a powertrain comprising at least one electric motor driven by the battery; a battery output current sensing circuit; and processing circuitry coupled to a battery output voltage sensing circuit and the battery output current sensing circuit, the processing circuitry configured to model behavior of the battery with at least first and second recurrent neural networks each comprising an input layer, a hidden layer, and an output layer, wherein a particular node of the hidden layer receives a first input from a node of the input layer and a second input from a previous time state of the hidden layer, wherein the first recurrent neural network models a predicted temperature of the battery, and wherein the processing circuitry provides the predicted temperature as input into the second recurrent neural network. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification