Ford Global Technolgoies, LLC

University of Michigan

The United States of America, by Sec. of the Army

Xinfan Lin

Richard Dyche Anderson

Yonghua Li

Anna G Stefanopoulou

Benjamin A Tabatowski-Bush

Tae-Kyung Lee

Yi Ding

Arnold Kweku Mensah-Brown

Matthew P Castanier

A method and a system of estimating core temperatures of battery cells in a battery pack can include several steps. In one step, a surface temperature of one or more battery cell(s) is received, a current of the one or more battery cell(s) is received, an inlet temperature of coolant provided to the battery pack is received, and a flow rate or velocity of the coolant is received. In another step, estimations are made including those of a cell-lumped internal electrical resistance of the battery cell(s), a cell-lumped conduction resistance between a core and a surface of the battery cell(s), and a cell-lumped convection resistance between the surface and the coolant. In yet another step, an estimation is made of a core temperature of the battery cell(s) based upon the received and estimated values of previous steps.

Estimating core temperatures of battery cells in a battery pack

A vehicle includes a traction battery and a controller coupled to the traction battery and having a memory, the controller being programmed to control the traction battery based on a difference between a total resistance indicated by voltage and current at a first operating condition and a battery cell resistance associated with the first operating condition previously stored in the memory, the difference being indicative of a wiring resistance associated with electrical connectors such as wires, cables, bus bars, and the like of the battery. The battery or the vehicle may be controlled in response to the adaptively determined wiring resistance by adjusting subsequent voltage or current determinations used to determine state of charge and battery capacity and/or to control charging or discharging of the battery and selection of various vehicle operating modes.

Adaptive identification of the wiring resistance in a traction battery

Systems and methods for sensing internal states of vehicle batteries are described. From this internal state information, various physical characteristics of the battery can be measured, calculated or inferred. A vehicle can include an electric motor, a battery to store electrical energy for the electric motor, and a sensor connected to the battery to sense a battery state, to receive an input signal, and to wirelessly transmit an output signal indicating the battery state. The sensor may be passive and built into the structure of the battery. The sensor can be a surface wave acoustic sensor with a magnetic field sensor, which can be a magnetoimpedance sensing device and a temperature sensor.

Sensor system for measuring battery internal state

A vehicle having a battery pack with cells arranged in at least groups of two cells in series is disclosed. A controller balances the cells based on a change in voltage across the cells being different than an expected change in voltage. The expected value is based on a current and a time associated with charging or discharging the cells. A controller is disclosed that commands charging and discharging of the battery cells based on a difference between a voltage across the group and the expected value for the group. A method for charging and discharging a battery pack is disclosed. The voltage across a group of cells is measured and compared to an expected value. An imbalance in a cell attribute is estimated according to a difference between the measured voltage and the expected voltage. The voltage across each battery cell is not required.

Detection of imbalance across multiple battery cells measured by the same voltage sensor

A vehicle includes a traction battery that is comprised of a number of cells. A controller operates the traction battery according to a temperature for each of the cells. The temperature is based on a number of coefficients representing a contribution of at least one cell boundary thermal condition and a heat generated in the cell to a steady-state temperature at a predetermined location within the cell. The contributions may be filtered to predict a dynamic response of the temperature to changes in the boundary thermal conditions and the heat generated in the cell. The coefficients may be derived from a full-order model. The resulting reduced-order model requires less execution time while achieving accuracy similar to the full-order model. In addition, a range of characteristic temperatures may be obtained for each cell.

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