TW201620228A - Battery charging method with temperature rise control - Google Patents

Abstract

A battery charging method with temperature rise control is disclosed. It includes the following steps: evaluating remaining battery capacity of a battery module by using a battery condition evaluation circuit; utilizing a temperature sensing circuit to measure temperature of the battery module for obtaining a temperature signal; executing a coarse charging current determination procedure and a fuzzy control procedure for generating a charging current value in accordance with the remaining battery capacity and the temperature signal. The charging current value decreases when the value of the temperature signal rises in the fuzzy control procedure, and the charging current value increases when the value of the temperature signal reduces in the fuzzy control procedure; and generating a charging current in accordance with the charging current value so as to charge the battery module.

Description

Battery charging method with temperature rise control

The present invention relates to a battery charging method, and more particularly to a battery charging method with temperature rise control.

As oil prices continue to rise, global warming and the greenhouse effect have intensified, making issues such as green environmental protection, energy conservation and carbon reduction attract the attention of countries all over the world, and the development and application of renewable energy and electric vehicles have become an inevitable trend. Since the development of these systems requires a large amount of battery energy storage and power supply system settings, the development of rechargeable battery manufacturing materials technology, charging technology, and power conversion and management technology has attracted attention.

Among battery-powered devices, methods for improving the performance and cost-effectiveness of their electrical energy storage systems can be divided into three categories: 1) advanced electrochemical properties and development of more environmentally friendly manufacturing materials; 2) charger circuit architecture And the improvement of charging efficiency; 3) possess intelligent charging and discharging control mechanism and power management capability. The charging method for rechargeable batteries in the research literature mentions various methods such as constant voltage charging method, constant current charging method, constant current-constant voltage (CC-CV) charging method, pulse charging method and Reflex ^TM charging method. The way to charge.

The most commonly used lithium-ion battery is charged as a constant current-constant voltage two-stage charging method. In the first stage, charging with a constant current can reach the desired voltage faster, and charging with a constant voltage in the second stage can make up for the first stage. The virtual charging phenomenon of current charging makes the battery more fully charged. It can also avoid battery damage caused by overcharging, but it still takes a long time to charge. Most of the chargers on the market use this method. Another challenge in charging methods is to design a universal charger that can cover different electrochemical properties. Therefore, the latest electronic technology uses a power management IC (PMIC) to control and regulate the power flow of the system to meet the power requirements of the load change. Achieve energy saving and extend battery life and longevity.

Having a fast charging mechanism is always a key consideration when designing battery-powered devices, so how to achieve high-performance fast charging has become the focus of design chargers. CC-CV cannot meet the requirements for fast charging because the CV phase delays the charging time and also reduces the energy conversion efficiency. Many studies have proposed different charging technologies and charging circuit topologies to solve this problem and meet the requirements of fast charging, such as: a full-bridge phase-shifting lithium battery charger architecture, which is controlled by a microprocessor to achieve CC-CV charging. Mechanism to achieve high output capacity and conversion efficiency; and a built-in resistor compensation method, which is used to switch CC mode to CV mode more smoothly, to more accurately allocate operating time of CC and CV modes, thereby improving charging The efficiency of the program.

In addition, there is a method of using a multi-stage constant current charging method to reduce the chemical reaction stress of the battery and shorten the charging time. However, the charging pattern obtained by the electrochemical behavior of the battery cannot guarantee an optimal solution. . Recently, intelligent charging algorithms, such as fuzzy, neuro-like, gray prediction, and gene algorithms, have been used to write into microcontrollers or custom ICs, integrated into charger control cores to improve chargers. Control the accuracy and operational performance of parameter prediction. These methods do improve the performance of the charger, but because the correctness of the algorithm must be built on the correct battery operation performance and accurate mathematical model, and the electrochemical characteristics of the battery are quite complicated, it is difficult to obtain accurate mathematical models. Therefore, only the improvement of the charging mode is not guaranteed to obtain the best charging pattern and can significantly improve its charging efficiency and shorten the charging. time.

In addition, searching for the best multi-stage charging current pattern for rechargeable batteries can be considered as a combination optimization problem, although using exhaustive search to try each combination can find the best solution, but exhaustive search is too time consuming and not expensive for engineers. economic. In order to solve this problem, it is known to use a global optimization technique such as a gene algorithm or an ant colony search method to search for a battery optimized multi-stage charging current pattern; and to optimize the Taguchi using a continuous orthogonal meter. The rule is to quickly get the best five-stage charging current pattern.

However, none of the above methods considers the temperature factor. The temperature rise caused by the battery during charging can be regarded as an energy loss. The higher the temperature rise, the greater the loss of energy, the worse the charging efficiency, and the battery is too high when charging, the battery is easy to accelerate aging, and it will be safe. problem. In addition, the aging phenomenon is independent of the number of charge and discharge cycles, but is caused by the internal resistance of the battery which gradually increases at a high temperature. Therefore, design developers can not only pursue the fastest charging time, but also how to ensure battery safety and battery life. In addition, for the built-in battery-type mobile device, the battery has more cycles, which can increase the time for using the mobile device, thereby prolonging the life and usage of the mobile device.

In order to solve the aforementioned problems, we need a novel battery charging method.

The main object of the present invention is to disclose a battery charging method with temperature rise control, which adjusts a charging current according to the remaining capacity of a battery to minimize the electrochemical reaction stress of a battery module.

Another object of the present invention is to disclose a battery charging method with temperature rise control, which uses a fuzzy control law to fine tune a charging current according to a temperature change of a battery module. Allows the battery to complete charging at a lower temperature rise to slow down battery aging and extend battery life.

To achieve the foregoing objective, a battery charging method with temperature rise control is proposed, which includes the following steps: a first step: estimating a remaining battery capacity of a battery module by using a state of charge estimation circuit; and a second step: utilizing a The temperature sensing circuit measures the temperature of the battery module to obtain a temperature signal; and the third step: performing a coarse charging current determining program by using a microcontroller to generate a rough charging current value according to the remaining battery capacity value, using one The processor executes a fuzzy control program to generate a fine charging current value according to a difference value of the temperature signal generated at each time interval and a difference value between the two adjacent time intervals. And using the microcontroller to add the coarse charging current value and the fine charging current value to generate a total charging current value, wherein the fuzzy control program decreases the fineness when the value of the temperature signal rises a charging current value that increases the fine charging current value when the value of the temperature signal decreases; and a fourth step: driving the synchronization with the microcontroller Buck converter according to the charge circuit to generate a charging current value of the total charging current to charge the battery module.

In one embodiment, the coarse charging current determining program generates the coarse charging current value according to a polynomial function of the remaining battery capacity value.

In an embodiment, the fuzzy control program employs a minimum inference engine.

In an embodiment, the fuzzy control program employs a sum centroid method to perform a defuzzification step.

In an embodiment, the battery charging method with temperature rise control further includes There is a step of using a human-machine interface to display a change in charging current with respect to time.

The detailed description of the drawings and the preferred embodiments are set forth in the accompanying drawings.

100‧‧‧Microcontroller

110‧‧‧Synchronous Rectified Buck Converter Charging Circuit

111‧‧‧First power switch

112‧‧‧second power switch

120‧‧‧Power State Estimation Circuit

130‧‧‧Battery module

140‧‧‧Temperature sensing circuit

150‧‧‧ processor

1 is a schematic diagram of a control system used in a battery charging method with temperature rise control according to the present invention.

2a is a circuit diagram of an embodiment of the synchronous rectification buck converter charging circuit of FIG. 1.

Figure 2a illustrates an equivalent circuit of Figure 1 in an energy storage phase.

Figure 2b illustrates an equivalent circuit of Figure 1 in an energy dissipating stage.

Figure 3a and Figure 3b show the charging completion schedule for different charging currents and different remaining capacities and the temperature rise table for different charging currents for different charging capacities.

FIG. 3c is a table showing the relationship between the time when the charging current 1C corresponds to 0.2C to 0.9C.

Figure 3d shows a table of residual capacity versus current.

Figure 4 shows the curve of the remaining capacity and charging current.

Figure 5 shows the fuzzy control architecture of the present invention.

Figure 6 shows the firmware architecture of the present invention.

7 and 8 are graphs showing comparisons of charging current and temperature rise in different charging methods.

Figures 9a and 9b show a comparison of experimental data of the present invention and conventional practices.

FIG. 10 is a flow chart showing an embodiment of a battery charging method with temperature rise control according to the present invention.

Please refer to FIG. 1 , which is a schematic diagram of a control system used in a battery charging method with temperature rise control according to the present invention. As shown in FIG. 1, the control system includes a microcontroller 100, a synchronous rectification buck converter charging circuit 110, a SOC-state of charge estimation circuit 120, a battery module 130, and a temperature. The sensing circuit 140 and a processor 150.

The microcontroller 100 is coupled to the power state estimation circuit 120 to obtain the remaining battery capacity information of the battery module 130 and determines a coarse charging current value, and is coupled to the processor 150 to obtain a fine charging current value. Then, a charging current value is determined according to the coarse charging current value and the fine charging current value. Thereafter, the microcontroller 100 determines a duty ratio of a pulse width modulation signal according to the charging current value to drive the synchronous rectification buck converter charging circuit 110 to generate a charging current to the battery module 130.

The synchronous rectification buck converter charging circuit 110 works as follows: a synchronous buck converter (SBC) mainly replaces a diode in a conventional buck circuit with a power switch and operates in a synchronous rectification manner. To reduce the diode conduction loss caused by the large inductor current. Referring to FIG. 2a, a circuit diagram of an embodiment of a synchronous rectification buck converter charging circuit 110 is shown. As shown in FIG. 2a, the synchronous rectification buck converter charging circuit includes a first power switch 111 and a second power switch 112. The following will analyze the continuous conduction mode (CCM) step-down operation: a) the first power switch 111 is turned on and the second power switch 112 is turned off: the equivalent circuit thereof is shown in FIG. 2b. As shown in FIG. 2b, in this state, since the voltage V _o on the output filter capacitor C is maintained, the voltage across the inductor is V _in -V _o , and the inductor L is stored by the input power source V _in . Since V _in >V _o , the inductor current i _L rises linearly and can be expressed as L(di _L /dt)=V _in -V _o (1)

When t=t _on , the inductor current reaches the maximum value i _L(max) . During the conduction of the first power switch 111, the variation of the inductor current Δi _L(+) can be expressed as Δi _L(+) =t _on (V _in -V _o )/L=DT _s (V _in -V _o )/L (2)

Where D is the duty ratio and T _s is the switching period.

b) The first power switch 111 is turned off and the second power switch 112 is turned on: its equivalent circuit is shown in Figure 2c. As shown in FIG. 2c, when the first power switch 111 is turned off, the second power switch 112 will be turned on to maintain the inductor current continuous. At this time, the inductor supplies energy to the load. Since the voltage across the inductor is -V _o , the inductor current i _L decreases linearly and can be expressed as L(di _L /dt)=-V _o (3)

When t=T _s , the inductor current reaches a minimum value of i _L(min) . During the second power switch 112 is turned on, the amount of change in the inductor current Δi _L(−) can be expressed as Δi _L(−) =t _off (-V _o )/L=(1-D)T _s (-V _o )/L (4)

If the inductor can maintain the volt-second balance operation, the net change of the inductor current for one cycle will be zero, then the output-to-voltage conversion ratio of the buck converter under CCM operation can be derived as Δi _L(+) + △ i _L(-) =DT _s (V _in -V _o )/L+(1-D)T _s (-V _o )/L=0 → V _o /V _in =D (5)

The state of charge estimation circuit 120 can employ an IC BQ20Z45, which is a wafer that conforms to the smart battery V1.1 specification. Using the 16-bit analog/digital converter inside the BQ20Z45, it can accurately measure the battery voltage, battery temperature, open circuit voltage and other related battery parameters of lithium-ion batteries and lithium polymer batteries, and use the system management bus line. To receive the command from the microcontroller 100. BQ20Z45 biggest feature is the tracking impedance (Impedance Track ^TM) technology, and complex impedance can be open-circuit voltage and the capacity of the counter, accurate prediction based on the capacity of the battery cell, the error is less than 1%.

The battery module 130 can include a plurality of lithium batteries and has a positive contact and a negative contact.

The temperature sensing circuit 140 is configured to measure the battery surface temperature of the battery module 130 and the indoor temperature to transmit a battery temperature information to the processor 150.

The processor 150 is configured to perform a fuzzy control rule according to the battery temperature information provided by the temperature sensing circuit 140 to determine a fine charging current value and transmit the same to the microcontroller 100.

The microcontroller 100 uses a residual capacity charging method to determine a coarse charging current value based on the remaining battery capacity (SOC) information. The principle is as follows: current charging technologies are faced with the problem of temperature rise, and temperature rise is the most important battery life. One of the direct factors. In addition, assuming that the charging current is 1C, when the remaining capacity is low, charging with 1C can indeed complete the fast charging, but when the remaining capacity is high, the charging rise with 0.9C and the charging completion time with 1C can reduce the temperature rise.

The remaining capacity charging method is a charging technology that can measure the SOC of a lithium ion battery to adjust the charging current, and the charging current can determine the required charging current value under different SOCs. Therefore, through experiments, it can be known that different charging currents (0.2C, 0.3C, 0.4C, 0.5C, 0.6C, 0.7C, 0.8C, 0.9C, 1C) are used to different residual capacities (0%, The charging completion time and the temperature rise required for charging the battery of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%). Figure 3a and Figure 3b show the charging completion schedule for different charging currents and different remaining capacities and the temperature rise table for different charging currents for different charging capacities.

From Fig. 3a, the relationship between the remaining capacity and the charging current and the effect of the known charging current on the battery temperature in Fig. 3b can be found, and the optimum charging current can be found. It can effectively control the temperature rise of the battery, and it can be similar to the charging time of the 1C charging current. From the charging time of 0.2C to 1C listed in Fig. 3a, the charging time of 1C is regarded as the numerator, and the charging time of 0.2C to 0.9C is regarded as the denominator, and the time ratio of 1C corresponding to 0.2C to 0.9C can be obtained respectively. The relationship is as shown in Figure 3c. After the establishment of the proportional relationship table, the optimal ratio of charging current can be determined, and the design goal is that the charging time is close to the shortest time. The design ratio of the present invention is 0.9, which represents a charging time close to 1C, corresponding to FIG. 3c. For the charging time ratio, the charging current of the ratio greater than 0.9 is shown in Figure 3d.

As can be seen from Fig. 3d, the charging current is in the interval of every 10% of the remaining capacity. In order to achieve a higher resolution charging current during charging, the curve of the residual capacity and current in Fig. 3d is used by the curve fitting function. For the purpose of fitting, the purpose is to establish a mathematical model via a limited sampling point and use this mathematical model for further analysis. Figure 4 shows the curve of the residual capacity and charging current; (6) is the mathematical model of the quadratic polynomial generation, and the coefficient of the curve fitting result is substituted to obtain the mathematical model of the remaining capacity percentage corresponding to the charging current.

I _ch =k ₁ (SOC) ³ +k ₂ (SOC) ² +k ₃ (SOC)+k ₄ (6)

In addition, the following describes the fuzzy control law executed by the processor 150 according to the battery temperature information provided by the temperature sensing circuit 140: in order to further control the battery temperature rise to slow down the aging, the fuzzy control law can adapt the charging current. Dynamic Adjustment. When the temperature rises, the amount of charging current is reduced. Otherwise, the amount of charging current is increased, so that the battery can be charged in a shorter time, and the temperature rise is lowered to slow down the aging. The input variable of the fuzzy control law is a temperature difference and a temperature difference variable of the battery, and the output variable is an increase/decrease value ΔI of the charging current, and the current increase/decrease amount is added to the previously obtained coarse adjustment current corresponding to the remaining capacity. , you can get the adaptive charge with temperature control mechanism The size of the electric current. Figure 5 shows the proposed fuzzy temperature rise controller architecture. Based on the charging experience of lithium-ion batteries, the temperature difference and the two-second temperature difference are planned as inputs, and each has five fuzzy subsets. The temperature difference fuzzy input divides the temperature difference characteristic into five fuzzy subsets, which are TS (Temperature Small; Low Temperature), TMS (Temperature Medium Small), TM (Temperature Medium), TML (Temperature Medium Large; High temperature) and TL (Temperature Large; high temperature). The fuzzy subset of temperature difference change rate is also divided into five fuzzy subsets according to the experimental experience, namely dT_NL (△T Negative Large; large negative temperature difference), dT_NS (△T Negative Small; small negative temperature difference), dT_Z ( ΔT Zero; zero temperature difference), dT_PS (ΔT Positive Small; small positive temperature difference) and dT_PL (ΔT Positive Large; large positive temperature difference). The output attribution function classifies the current trimming amount from small to large into five fuzzy subsets, which are ΔI_NL (△I Negative Large; large negative current trimming amount), △I_NS (△I Negative Small; small negative current trimming). Quantity), ΔI_Z (ΔI Zero; zero current trimming amount), ΔI_PS (ΔI Positive Small; small positive current trimming amount) and ΔI_PL (ΔI Positive Large; large positive current trimming amount), and each The median values of the fuzzy subsets are -10%, -5%, 0%, 5%, and 10%, respectively.

The rule base is generally designed according to user experience and expertise, and then converted into a language control law, which can be used to describe the relationship between system input and output. The dual input fuzzy controller used in the present invention, wherein the two attribution functions each have 5 fuzzy subsets, so there will be 25 (5X5) rules. At present, the inference engine of fuzzy theory has many forms, including minimum inference, maximum inference, maximum product inference, maximum boundary inference, etc., among which the smallest inference is the most common. The invention hereby takes the smallest inference engine as an embodiment.

Defuzzification is the last step in the operation of the fuzzy control law to convert the output subsets of different attributions into quantized numerical outputs using different computational methods. Currently used solutions There are many methods for fuzzification, including the maximum averaging method, the center averaging method, the center of sum (COS), and the center of area (COA). Here, the present invention takes the sum of gravity center method as an embodiment.

Firmware architecture:

The invention uses the microcontroller 100 as a control core, and its firmware architecture is as shown in FIG. 6. First, I ² C is used to communicate with the state of charge estimation circuit 120 to read information such as battery voltage, current, and remaining capacity, and the battery information is transmitted from the RS-232 serial communication module to the LabVIEW human machine interface of the processor 150, and then The temperature sensing circuit 140 is used to read the surface temperature of the battery and the indoor temperature, and the fuzzy controller is implemented by LabvVIEW, and the current fluctuation amount (ΔI) is output, and then the current fluctuation amount (ΔI) is transmitted to the microcontroller 100 by RS-232. And adding the rough charging current corresponding to the SOC that has been established in the microcontroller 100, and controlling the PWM duty cycle of the required output by the incremental PID operation, which can be appropriately adjusted as the ambient temperature changes. Charge current to achieve fuzzy control charging and monitoring by the LabVIEW HMI. In addition, the LabVIEW Human Machine Interface displays a change in charge current versus time.

Experimental results:

Fig. 7 and Fig. 8 are graphs of charging current and temperature rise comparison of different charging methods. It can be seen from Fig. 8 that after the addition of the fuzzy temperature rise control, the temperature rise of the battery charging is effectively reduced, as shown in Fig. 9a, CC-CV The average temperature rise of the charging method is 5.539 ° C, the average temperature rise of the remaining capacity charging method is 4.468 ° C, and the average temperature rise of the residual capacity charging method (ΔI=10%) of the fuzzy control is 4.041 ° C, and the remaining capacity of the fuzzy control is charged. The average temperature rise of the method (ΔI = 20%) was 3.822 °C.

As shown in the comparison result of Fig. 9b, it can be seen that although the conventional CC-CV charging method has the shortest charging time, the charging temperature is increased and the charging efficiency is low; the charging time of the remaining capacity charging method is The charging time division ratio of CC-CV charging method is 0.885, which is close to the expected 0.9, and the charging efficiency is increased by 1.62%; the charging time ratio of fuzzy control (△I=10%) is 0.858, fuzzy control (△I=20) The charging time ratio of %) is 0.838, and the charging efficiency is increased by 1.76% and 2.06%, respectively.

The temperature rise change part, as shown in Fig. 8 and Fig. 9a, compares the three groups of charging methods with the traditional CC-CV, and the average temperature rise of the remaining capacity charging method is reduced by 18.5%, and the fuzzy control residual capacity charging method (ΔI=10%) The average temperature rise is reduced by 23.2%, and the average temperature rise of the fuzzy control residual capacity charging method (ΔI=20%) is reduced by 31.24%. Therefore, the remaining capacity charging method combined with the fuzzy control proposed by the present invention can effectively improve the charging efficiency and lower the maximum temperature rise and the average temperature rise of the charging, although the charging time is longer than the CC-CV charging method.

According to the above description, the present invention proposes a battery charging method with temperature rise control, and the flow thereof is shown in FIG. As shown in FIG. 10, the process includes the following steps: estimating a remaining battery capacity of a battery module by using a power state estimation circuit (step a); measuring a temperature of the battery module by using a temperature sensing circuit to obtain a a temperature signal (step b); performing a coarse charging current determination procedure by a microcontroller to generate a coarse charging current value based on the remaining battery capacity value, using a processor to perform a fuzzy control program to a difference value generated by a time interval and a difference between the change values between each two adjacent time intervals generates a fine charging current value, and the coarse charging current value is summed by the microcontroller The fine charging current value is to generate a total charging current value, wherein the fuzzy control program decreases the fine charging current value when the value of the temperature signal rises, and increases when the value of the temperature signal decreases The fine charging current value (step c); and driving a synchronous rectification buck converter charging circuit with the microcontroller to generate a charging current according to the total charging current value Charging the battery module (step d).

According to the above technical solution, the present invention can provide the following effects:

1. The battery charging method with temperature rise control of the present invention can adaptively adjust a charging current according to the remaining capacity of a battery to minimize the electrochemical reaction stress of a battery module.

2. The battery charging method with temperature rise control of the present invention can utilize a fuzzy control rule to finely adjust a charging current according to the temperature change of a battery module, so that the battery can be charged at a lower temperature rise to slow down the battery aging and prolong the battery. Battery Life.

The disclosure of the present invention is a preferred embodiment. Any change or modification of the present invention originating from the technical idea of the present invention and being easily inferred by those skilled in the art will not deviate from the scope of patent rights of the present invention.

In summary, this case, regardless of its purpose, means and efficacy, is showing its technical characteristics that are different from the conventional ones, and its first invention is practical and practical, and it is also in compliance with the patent requirements of the invention. Pray for the patents at an early date.

Claims (5)

A battery charging method with temperature rise control, comprising the following steps: first step: estimating a remaining battery capacity of a battery module by using a power state estimation circuit; and second step: measuring the battery by using a temperature sensing circuit The temperature of the module obtains a temperature signal; the third step: using a microcontroller to perform a coarse charging current determining program to generate a coarse charging current value according to the remaining battery capacity value, and executing a fuzzy control program by using a processor Generating a fine charging current value according to a difference between a change value generated by the temperature signal at each time interval and the change value between every two adjacent time intervals, and summing up using the microcontroller The coarse charging current value and the fine charging current value to generate a total charging current value, wherein the fuzzy control program decreases the fine charging current value when the value of the temperature signal rises, at the temperature The value of the signal decreases to increase the value of the fine charging current; and the fourth step: driving the synchronous rectification buck converter charging circuit with the microcontroller The total value of the charging current generating a charging current to charge the battery module. The battery charging method with temperature rise control according to claim 1, wherein the rough charging current determining program generates the coarse charging current value according to a polynomial function of the remaining battery capacity value. A battery charging method with temperature rise control as described in claim 1, wherein the fuzzy control program employs a minimum inference engine. The method for charging a battery with temperature rise control according to claim 1, wherein The fuzzy control program uses a minimum inference engine. The battery charging method with temperature rise control according to claim 1, wherein the fuzzy control program uses a sum centroid method to perform a defuzzification step. The battery charging method with temperature rise control according to claim 1, further comprising the step of displaying a change of a charging current with respect to time by using a human machine interface.