Abstract: Described herein is a wireless charging system including switched capacitor (SC) rectifiers with output regulation. The load for the receiver on mobile devices using wireless charging is a battery. Regulation is needed for battery charging applications, e.g. constant voltage charging, constant current charging, and pulsed charging. For this purpose, the wireless power transfer (WPT) receiver can possess some “intelligence” to monitor the output voltage/current, adjust the behavior of the electronic circuitries and achieve a closed-loop control. Because a multilevel switched-capacitor (MSC) rectifier has output control ability, this can allow the MSC rectifier to directly charge the battery without an additional DC/DC charger on-board the device.

Abstract: Described herein is a wireless charging system including switched capacitor (SC) rectifiers with output regulation. The load for the receiver on mobile devices using wireless charging is a battery. Regulation is needed for battery charging applications, e.g. constant voltage charging, constant current charging, and pulsed charging. For this purpose, the wireless power transfer (WPT) receiver can possess some “intelligence” to monitor the output voltage/current, adjust the behavior of the electronic circuitries and achieve a closed-loop control. Because a multilevel switched-capacitor (MSC) rectifier has output control ability, this can allow the MSC rectifier to directly charge the battery without an additional DC/DC charger on-board the device.

Abstract: An apparatus for model predictive control (“MPC”) is disclosed. A method and system also perform the functions of the apparatus. The apparatus includes a measurement module that receives battery status information from one or more sensors receiving information from a battery cell, and a Kalman filter module that uses a Kalman filter and the battery status information to provide a state estimate vector. The apparatus includes a battery model module that inputs the state estimate vector and battery status information into a battery model and calculates a battery model output, the battery model representing the battery cell, and an MPC optimization module that inputs one or more battery model outputs and an error signal in a model predictive control algorithm to calculate an optimal response. The optimal response includes a modification of the error signal.

Abstract: An apparatus includes a battery state module that determines a battery state of each of a plurality of battery cells forming a battery unit. A battery state includes a health of the battery cell. A battery state of a battery cell differs from a battery state of other battery cells of the battery unit. Each battery cell is connected to a shared bus through a bypass converter that provides power from the battery cell to the shared bus. A charge/discharge modification module determines, based on battery state, an amount to vary a charging characteristic for each battery cell compared to a reference charging characteristic. Each charging characteristic varies as a function of a reference state. A charge/discharge module adjusts charging/discharging of a battery cell of the battery unit based on the charging characteristic of the battery cell.

Abstract: For battery control, an apparatus includes a shared bus and a plurality of isolated direct current (DC) to DC bypass converters. Each bypass converter is associated with one battery unit. Inputs of each bypass converter are in parallel electrical communication with the associated battery unit. Outputs of each bypass converter are in parallel electrical communication with the shared bus. Each bypass converter estimates a battery state for each battery unit and controls the battery state to a reference state.

Abstract: An apparatus for model predictive control (“MPC”) is disclosed. A method and system also perform the functions of the apparatus. The apparatus includes a measurement module that receives battery status information from one or more sensors receiving information from a battery cell, and a Kalman filter module that uses a Kalman filter and the battery status information to provide a state estimate vector. The apparatus includes a battery model module that inputs the state estimate vector and battery status information into a battery model and calculates a battery model output, the battery model representing the battery cell, and an MPC optimization module that inputs one or more battery model outputs and an error signal in a model predictive control algorithm to calculate an optimal response. The optimal response includes a modification of the error signal.

Abstract: An apparatus includes a battery state module that determines a battery state of each of a plurality of battery cells forming a battery unit. A battery state includes a health of the battery cell. A battery state of a battery cell differs from a battery state of other battery cells of the battery unit. Each battery cell is connected to a shared bus through a bypass converter that provides power from the battery cell to the shared bus. A charge/discharge modification module determines, based on battery state, an amount to vary a charging characteristic for each battery cell compared to a reference charging characteristic. Each charging characteristic varies as a function of a reference state. A charge/discharge module adjusts charging/discharging of a battery cell of the battery unit based on the charging characteristic of the battery cell.

Abstract: For battery control, an apparatus includes a shared bus and a plurality of isolated direct current (DC) to DC bypass converters. Each bypass converter is associated with one battery unit. Inputs of each bypass converter are in parallel electrical communication with the associated battery unit. Outputs of each bypass converter are in parallel electrical communication with the shared bus. Each bypass converter estimates a battery state for each battery unit and controls the battery state to a reference state.