Battery Management Systems for Electric Vehicles

Determining short circuit risk in battery cells after manufacturing to reduce fire hazards. The technique involves monitoring self-discharge current and voltage during cell standby periods to calculate a total resistance. If the calculated resistance is below a threshold, it indicates accelerated short circuit degradation and raises a short circuit risk alert.

Source

Compact power electronics device for controlling batteries in electric vehicles that reduces size and cost compared to using standard DCDC converters. The device is a printed circuit board (PCB) with integrated power electronics to control battery cells. The DCDC converter on the PCB has a compact planar layout formed directly on the substrate. Features like a closed loop primary winding, integrated leakage inductance, planar integrated transformer, modular secondary winding, and rectifier variants allow high power output with fewer components. The planar geometry enables a thickness less than 1mm.

Source

Control method for charging facilities to enable stable charging of batteries even when the charging facility output voltage is lower than a minimum limit. The method involves transmitting an outputtable current value from the charging facility to the vehicle. The vehicle sets a charging current command based on this value. The charging facility then uses the command to supply charging power to the battery. The outputtable current is set to decrease as the battery voltage drops. This widens the charging range and allows stable charging of low-voltage batteries, even if the facility output voltage is below the minimum limit.

Source

A system to optimize electric vehicle (EV) charging by dynamically allocating charging stations based on vehicle battery size and charge rate. The system involves communication between EVs and charging stations using wireless signals. The EVs transmit their battery level, draw rate, destination, and charge capacity. The stations stack this data against their current status to determine optimal charging assignments. This allows faster, more efficient, and fairer utilization of charging infrastructure by matching EV needs to station capabilities.

Source

Early detection of thermal runaway events in batteries, like those used in electric vehicles, by detecting the initial venting of gases during the runaway process. A sensor measures the thermal conductivity of the gas atmosphere inside the battery. Changes in conductivity due to venting can be detected as an indicator of an impending thermal runaway. An apparatus with interface and processing circuitry receives the conductivity measurement and determines if venting has occurred. This allows early warning of potential thermal runaway events to mitigate safety risks.

Source

Battery control system that improves battery charging and discharging reliability and efficiency by accurately determining charging and discharging limits based on real-time battery conditions. The system predicts internal resistance based on projected operating conditions, but switches to using real-time measured internal resistance if the battery voltage is above a threshold. This prevents overcharging and undercharging by better matching the actual battery resistance.

Source

Detecting the cause of discharging a vehicle battery by waking up a control module when a vehicle controller draws more current. The waking module identifies the first controller that powered on, then determines if other controllers should be sleeping but aren't. This allows finding devices that keep the battery drained when supposed to be off.

Source

Intelligent battery charge depletion system for range-extended electric vehicles (REEVs) that optimizes battery charging strategy based on estimated vehicle load. The system monitors battery state of charge, road load, and gross vehicle weight. It determines a modified charge depletion setpoint that increases as load increases, maintaining a torque reserve. This prevents premature depletion when load is low. The engine recharges the battery. It's more efficient than fixed charge depletion or sustained charging.

Source

Monitoring swelling of battery containers without internal sensors by attaching an external strain gauge to a tightening strap around the battery. The strap has a tightening mechanism to pull it taut against the battery container when swelling occurs. The strain gauge stretches with the container expansion and is connected to an electronics package that reads the gauge and transmits the strain data to a battery management system.

Source

Thermal runaway detection and control for lithium-ion batteries to prevent battery fires and explosions. The method involves mounting palladium-based nano sensors on individual battery cells to detect hydrogen concentrations. If hydrogen levels exceed a threshold, charging/discharging is stopped. If hydrogen stays below another threshold, charging/discharging resumes. This allows selective cell shutdown and restart based on hydrogen levels, preventing thermal runaway spread.

Source

Isolation resistance monitoring for battery management systems (BMS) in electric vehicles (EVs) that enables accurate and cost-effective isolation resistance measurement for both the high-voltage (HV) battery pack and the floating high-voltage link side when disconnected. The monitoring uses a single device and power supply powered from the 12V auxiliary voltage of the EV. The device applies a test voltage from the auxiliary supply to a resistor, measures the resulting current, and calculates the isolation resistance. This allows isolation resistance monitoring for both the HV pack and link sides using just one device and power source, simplifying and reducing cost compared to separate monitoring for each side.

Source

Reliable diagnosis of low battery voltage in electric vehicles to prevent cell swelling and fires. The method involves differentiating between low voltage and disconnection diagnosis. It uses a higher threshold voltage and longer time duration for low voltage diagnosis versus disconnection diagnosis. This prevents misdiagnosis when cells rapidly drop voltage due to degradation vs. disconnection. The battery diagnosis system also performs low voltage diagnosis regardless of disconnection diagnosis results if cell voltage meets the entry condition. This improves reliability compared to traditional methods that only diagnose low voltage when cell voltage stays below 1.5V for 5 seconds.

Source

Early warning system to detect thermal runaway in electric vehicle batteries using acoustic sensors. The system monitors sound waves emitted from battery cells to predict thermal runaway before it escalates. Acoustic sensors detect low frequency infrasound generated by gas bubbles forming during early stages of thermal runaway. An algorithm analyzes the acoustic data to predict thermal runaway. This allows earlier intervention to prevent escalation compared to temperature sensors.

Source

Compensating open circuit voltage (OCV) of a battery to improve accuracy of battery state estimation algorithms, especially for aging batteries. The compensation is based on monitoring the voltage peaks in the cell's voltage range over cycling. By tracking the peak voltage and its SOC each cycle, and the peak voltage variation, the compensation factors are determined. This allows precisely adjusting the OCV for a given SOC based on the aging characteristics of the specific cell.

Source

Battery diagnosis system for electric vehicles that can accurately diagnose voltage deviations in batteries, even when voltage suddenly drops due to severe cell degradation. The diagnosis is performed differently depending on whether the cell voltage is normal or abnormal. If abnormal, output power is limited. This prevents continued use of degraded batteries that could lead to fires. If normal, output power is limited more to mitigate potential issues. The differentiated diagnosis and response allows more effective battery management and safety for electric vehicles.

Source

Calculating battery depth of charge without disassembling the battery cell using the internal resistance. The method involves computing the internal resistance of the battery cell during charging based on the voltage and current during charging. The internal resistance at different charge rates is calculated. Then, the negative electrode depth of charge is determined by comparing the computed internal resistance to a reference value. This allows calculating the depth of charge of a full cell without needing to disassemble and test individual electrodes.

Source

Accurate internal resistance evaluation for battery packs with multiple banks to mitigate errors due to contact and coupling resistances. The method involves analyzing the internal resistance values of the banks in each pack to identify any abnormal banks with higher resistance. Then, correcting the internal resistance of the identified bank using the resistance values of the other banks. This compensates for the mechanical resistances affecting the cell voltages. By identifying and correcting specific banks with high resistance, it reduces the overall internal resistance measurement error.

Source

Accurately diagnosing battery cell failures in a pack during charging by monitoring internal resistance changes. The method involves determining internal resistance values for each cell during charging using the current and voltage changes from a specific request time when the pack voltage reaches a threshold. This allows distinguishing resistance increases due to deterioration versus defects. Deviations in the cell-specific resistance values indicate defects.

Source

A battery abnormality detection system that can accurately detect micro-short circuits in batteries like lithium-ion iron phosphate (LFP) batteries that have a large plateau region in their voltage vs. state of charge (SOC) curve. The system estimates dV/dQ, the derivative of voltage with respect to charge, for each cell or cell block during charging. It looks for changes in dV/dQ variation between cells/blocks as an indicator of micro-short circuits. This provides more accurate detection compared to voltage or SOC changes since LFP batteries have a flat voltage region where those methods are less effective.

Source

A drive circuit for electric vehicle batteries that prevents unexpected resets during driving from causing safety issues. The circuit has a delay module and a low-side driver module. When the control module resets, the delay module delays the low-side driver module's input signal by a preset duration. This maintains the low-side driver's previous state during reset, preventing unintended switching. The delay is implemented using cascaded delay flip-flops.

Source