An intelligent battery management system and method, cutting-in at a new angle, optimizes rechargeable battery set to the best performance, which can overcome the backwards of all current management systems and methods, and reduce the manufacturing cost at better performances. The management system is supported by a cutting-edge method and corresponding embodiment, which can automatically re-combine batteries in a battery set in parallel connection or in series connection or in mixed series-parallel connection, or mixed parallel-series connection, each individual cell in a battery set can accessed, which means each individual cell can be monitored (i.e. its parameters can be measured) and charged or discharged. With this system, batteries can be charged or discharged to their best performance.
Battery management system (BMS) is an important part of the Electric Vehicle (EV). It protects the battery system from damage, predicts and increases battery life, and maintains the battery system in an accurate and reliable operational condition. The BMS performs several tasks such as measuring the system voltage, current and temperature, the cells state of charge (SoC), state of health (SoH), and remaining useful life (RUL) determination, protecting the cells, thermal management, controlling the charge/discharge procedure, data acquisition, communication with on-board and off-board modules, monitoring and storing historical data and the most important task is the cell balancing. Imbalance of cells in battery systems is very important matter in the battery system life. Because without the balancing system, the individual cell voltages will drift apart over time. The capacity of the total pack will also decrease more quickly during operation then fail the battery system. As mentioned in cited papers [1-2], currently, the most common methods of battery management are passive and active cell balance or equalization, which have been reviewed in [3-7] and described the related US patents listed below. However, none of these methods can access individual battery subset or single battery for measuring, monitoring and balancing, and compensation. The intelligent battery management system and methods of this intervention can solve the problem.
An intelligent battery management system and method, cutting-in at a new angle, optimizes rechargeable battery set to the best performance, which can overcome the backwards of all current management systems and methods, and reduce the manufacturing cost at better performances. The management system is supported by a cutting-edge method and corresponding embodiments, which can automatically re-combine batteries in a battery set in parallel connection or in series connection or in mixed series-parallel connection, or mixed parallel-series connection, each individual cell in a battery set can accessed, which means each individual cell can be monitored (i.e. its parameters can be measured) and charged or discharged. With this system, batteries can be charged or discharged to their best performance. Besides battery set, the system comprises connection controller [the combined connection controller, or parallel connection controller and series connection controller], micro-processor/controller, meters for battery measurement and monitoring, charger, load serve pack (electrical and mechanical), and thermal management apparatus.
The system comprises battery set 100, connection controller [i.e. the combined connection controller 200, or parallel connection controller 300 and series connection controller 400, as show in
Battery connection controller is the apparatus embodiments for arbitrarily controlling battery connection. In
Connection controller is one of the key elements of this invention. In
Let's assume there are total Nb battery units, Nset battery subsets, and there are Nsb battery units in each subset, so Nset×Nsb=Nb, we need further to group these Nset battery subset into Ns rows in series connection, Np battery units inside each row in parallel connection, or to group these Nset battery subset into Np columns in parallel connection, Ns battery units inside each column in series connection, so Ns×Np=Nset, and Nsb×Ns×Np=Nb. Each battery unit is single battery along, or a single battery with balance/compensation device together. For example, Tesla RoadStar has 6831 battery, 69 cells are wired in parallel to create a brick, 9 (i.e. 3×3) bricks are connected in series to create sheets, and 11 sheets are inserted in series into the pack casing, in total, this creates a pack made up of 6,831 cells, which means Nsb=1, Np=69, and Ns=99 (3×3×11).
In
In
Let's give more description on
For 4 level control voltages (in
For 5 level control voltages (in
II. Separate Connection Controllers
Unlike the combined connection controller 200, parallel connection controller 300 and series connection controller 400 can be built separately, as shown in
The function in
In
Using this invented apparatus and method, either each battery subset or each single battery (if subset has only single battery, which means without using battery subset) can be accessed by monitoring instrument and its electrical and electrochemical parameters (such as voltages [open & load], current, resistances [discharge, ohmic←electrolyte & electronic types, non-ohmic or nonlinear, etc.], impedances and impedance spectrum, electric capacity and discharge capacity, SOC[state of capacity], SOH[state of healthy], etc.) can be measured and be monitored as long as the micro-controller select this subset. The monitoring and measuring process can be done every day, or even moment when battery is not at loading or recharging, such as when waiting at red light. Measurement or monitoring is rotated subset by subset or is continued from the measurement for last subset, and result for each subset is stored and updated timely.
As mentioned above, either each battery subset or each single battery (means without using “battery subset”) can be accessed by monitoring instrument. However, if selecting the latter, i.e. applying connection controller described above to access EVERY SINGLE battery unit without using “buttery subset”, it is very cost and reduces the product competition power (of course, we can build a system in this way if cost is not an issue); while on the other hand, if selecting the former, i.e. applying connection controller described above to access every battery subset, without special treatment, each single battery units inside each battery subset cannot be directly accessed by monitoring instrument. The special treatment described below will solve this problem.
In
Unlike the monitoring and measuring process for battery subsets, as mentioned before, which can be done every day, or even every moment when battery is not at loading or recharging. For single battery inside a subset, measuring, monitoring, adjustment, and re-combination process can be done every month, or on very weekend. According to measured results, battery in one subset may be made an adjustment or/and re-combination, i.e. exchange location with battery in another subset or with battery within same subset, to get an optimization configuration.
Using invented embodiments, batteries can be arbitrarily connected, either in series, or in parallel, and the number battery subsets and number of single batteries in a subset can be arbitrarily assigned. Regarding how to connect, i.e. how many batteries are assigned in a subset and these batteries in a subset are connected in parallel or in series, or in mixed, and how many battery subsets are used in series connection in a branch and many parallel branches are assigned, or how many battery subsets are used in parallel connection in a layer and many series layers are assigned, . . . and so on, it is completely determined by modeling analysis and optimization of recharging and loading (including the balance elements and motor inductance together), which is based on the measurement or monitoring data of batteries. The detail of modeling analysis and optimization algorithms for recharging and loading varies from case to case of application. The optimization is based on impedance and other parameters, which describe battery's performance, also including motor inductance and balance elements. In the below, only a simple and strait forward example is given to illustrate the basic idea of management, and what optimization of configuration for battery connection means, but actually detail algorithms are much complex than what described in this example from here below.
Assume we have 8000 Li-ion batteries with average open voltage 3.2 Volts, and their intern resistances have a distribution (from larger, median, to smaller). If design motor working at 320 Volts, then we need a connection matrix of battery to achieve this goal and there are many connection ways to do that, here we show three direct or straight forward ways: the 1st way, parallel connection before series connection, is dividing 8000 batteries into 100 groups, and connect 80 batteries in parallel (80 columns) in each group, and then connect all 100 groups in series (100 rows); the 2nd way, series connection before parallel connection, is diving 8000 batteries into 80 groups, and connect 100 batteries in series in each group, then connect all 80 groups in parallel; the 3rd way is diving 8000 batteries into 10 (rows)×10 (columns) subset battery matrix, and each battery subset is consist of 10 (rows)×8 (columns) single battery matrix. Actually, the 3rd way includes 4 different compositions (ways) as shown in the table below:
Actually, the 3rd way can be extended to many ways, i.e. diving 8000 batteries into n1 (rows)×m1 (columns) subset battery matrix, and each battery subset is consist of n2 (rows)×m2 (columns) single battery matrix, with constrains n1×n2=100 and m1×m2=80. The integral solutions of n1×n2=100 are 1×100, 2×50, 4×25, 5×20, 10×10 (total 5 solutions); The integral solutions of m1×m2=80 are 1×80, 2×40, 4×20, 5×16, 8×10 (total 5 solutions), so there are 5×5×4=100 ways extended from the 3rd way. Further more, the 3rd way only include one level battery subset. It can be extended to even more ways by including more levels of battery subset, such as, sub-subset in a subset, and sub-sub-subset in a sub-subset, . . . and so on . . . and there are total a few hundreds ways to connect these 8000 batteries.
As we already seen above, extended from the 3rd ways above, there are total a few hundreds ways to connect these 8000 batteries, the optimization means finding out the best way for the application from these hundreds composition ways (circuits), and within the best way (circuit), finding out best combination (for cell matching) for all individual battery cells. Therefore optimization needs help from programming or modeling and it is complex to describe through language. However, optimization idea can described through a simple example applied on the way and the 2nd way.
Let's talk about the 2ad way first in the below, because it is straightforward. As we know that, open circuit voltage of battery is a nonlinear, but monotonic function of SOC. So if open-circuit voltages are matched, the subsets or batteries will have equal SOC. Under loading, terminal voltage will vary significantly from open-circuit voltage due to internal impedance of battery or subset, which is again a nonlinear function of SOC. If all of the batteries in a column are properly managed through re-combination by connection controller of this invention, their internal impedances should be nearly equal. We can simply group batteries by impedance, so that, within each column, every batteries have almost same internal impedance, but different column has different total internal impedance, then when re-charging voltage is applied, the voltages divided onto each battery in a column are almost same, but different column is assigned different current according to different total impedance—the column with smaller impedance (corresponding higher SOC) passes more current and so gets more charged energy—which is consistent with higher capacity even if without help from balance elements (or circuits) and equalization, so all columns can reach their maximum charging at almost same time. Without this procedure, once any one bad battery in the matrix reach it's maximum charging, the re-charging process must stop for all battery, even if most of the batteries are far away from completely charged, in this case, balance elements and equalization is a must, but cost is much higher. When discharging with load, the batteries need to be re-connected, so that, within each column, the every batteries have closest SOC (not necessary completely consistence with impedance due to battery intrinsic complexity), but different column has different total SOC, the SOC's of some of them are larger, but some are smaller. Considering battery prefers working at smaller current (longer life time), the invented management system will use all batteries, i.e. all columns, when automobile is speeding up [need more power], or climbing up steep hills, so that each battery works at smallest current. However, when automobile is driving on flat road, or at low speed, management system will not use all battery columns, again, considering battery prefers working at smaller current, the management system only excludes only one, or two, or a few (but “one” may be the best) battery column with lowest SOC from loading, i.e. the management system always picks out the column with lowest SOC, and exclude it from the loading at low power consuming state. May be 5 minute later, this one is longer the one with lowest SOC, the system will pick out a new one with lowest SOC for instead. In this way, the stored energy of all batteries can be almost completely used before next re-charging. In the example of 8000 battery cells mentioned above, there are 100 rows and 80 columns. After exclude the 1 column with lowest SOC, there are 79 columns left for loading, so we could use either the 1st way (parallel connection before series connection) or the 2nd way (series connection before parallel connection) to composite the 100 rows×79 columns battery matrix.
The 1st way functions almost same as the 2nd way except it has local self-compensation within each row through parallel connections of every internal layer. While, the 2nd way does not have because the parallel connections are only at the two outside terminals (no internal parallel connections). As mentioned above, we can group batteries with closest internal impedance or closest SOC in same column, bases on this assignation, we could further assign the batteries for each rows so that all the rows have closest total impedance 1/[1/Zk1+1/Zk2+1/Zk3+ . . . +1/Zk79] (still using the 8000 cells example above, where k=1, 2, 3, . . . , 100). Whatever in re-charging or discharging, within a row, a cell with smaller impedance (larger SOC) will pass more current, while a cell with larger impedance (smaller SOC) will pass less current, which is equivalent to a local current cycle (around average) from larger SOC cell to small SCO cell, canceling the latter current (re-charging) and enhancing the former current—this is so called local self-compensation.
“Hole-net thermal bed” is a preferred embodiment for thermal management. The individual cells within a battery set differ due to manufacturing variations, temperature gradients, and aging effects (also temperature dependent). Therefore, battery or battery subset need to be installed in a thermal bed, which is made up of good thermal conduct material, such as copper, Aluminum, etc. Inside the walls of battery thermal bed, there is hole-net (i.e. many air flow channels) which is connected to thermal controlling system, the air with almost same temperature is conducted to thermal beds of all batteries through the hole-net, so that all of the battery have almost same temperature as the battery bed, which eliminates the temperature gradients (cell to cell and inside every cell) at the best situation. When starting use of battery at cold weather, the heating system
The application claims the priority from U.S. provisional application No. US 61/685,990, filed on Mar. 29, 2012 with post mail date on Mar. 27, 2012, and tilted “Battery Management System and Method for Optimizing Battery Set to the Best Performance”.