LR1130 battery.What is the core technology of BMS power battery management system?

　　What is the core technology of BMS?

　　I recently saw a promotional sign from a domestic company claiming to fully master the battery management system (BMS) software and hardware technology, reach the world's advanced level, and adopt multiple equalization control capabilities because of its use of underlying software such as AUTOSAR's software architecture. Very eye-catching. Are these the core technologies of BMS?

　　Usually, the BMS system usually includes a detection module and arithmetic control module.

　　Detection refers to measuring the voltage, current and temperature of the cell and the voltage of the battery pack, and then transmitting these signals to the computing module for processing and issuing instructions. Therefore, the computing control module is the brain of BMS. The control module generally includes hardware, basic software, runtime environment (RTE) and application software. The most core part - application software. The environment developed with Simulink is generally divided into two parts: battery status estimation algorithm and fault diagnosis and protection. State estimation includes SOC (State Of Charge), SOP (State Of Power), SOH (State of Health), as well as balancing and thermal management.

　　Battery status estimation usually estimates SOC, SOP and SOH. SOC (state of charge) simply means how much power is left in the battery; SOC is the most important parameter in BMS, because everything else is based on SOC, so its accuracy and robustness (also called error correction ability) is extremely important. If there is no accurate SOC, no matter how many protection functions are added, the BMS will not be able to work properly, because the battery will always be in a protected state, and the life of the battery will not be extended.

　　In addition, the estimation accuracy of SOC is also very important. The higher the accuracy, the higher the cruising range can be for a battery of the same capacity. Therefore, high-precision SOC estimation can effectively reduce the required battery cost. For example, Chrysler's Fiat 500e BEV can always discharge SOC=5%. It became the electric vehicle with the longest range at that time.

　　The figure below is an example of the robustness of the algorithm. The battery is a lithium iron phosphate battery. Its SOCvs OCV curve only changes about 2-3mV in the SOC range from 70% to 95%. The measurement error of the voltage sensor is 3-4mV. In this case, we intentionally let the initial SOC have a 20% error to see if the algorithm can correct the 20% error. If there is no error correction function, SOC will follow the SOCI curve. The SOC output by the algorithm is CombinedSOC, which is the solid blue line in the figure. CalculatedSOC is the real SOC that is deduced based on the final verification results.

　　SOP is the maximum discharge and charging power that the battery can provide at the next moment, such as the next 2 seconds, 10 seconds, 30 seconds, and continuous high current. Of course, the impact of continuous large current on the fuse should also be considered.

　　Accurate estimation of SOP can maximize battery utilization efficiency. For example, when braking, it can absorb as much feedback energy as possible without damaging the battery. When accelerating, it can provide more power to obtain greater acceleration without damaging the battery. At the same time, it can also ensure that the car will not lose power due to under-voltage or over-current protection during driving, even when the SOC is very low. In this way, the so-called first-level protection and second-level protection are just a passing thing in the face of precise SOP. That’s not to say protection isn’t important. Protection is always needed. But it cannot be the core technology of BMS. Accurate SOP estimation is especially important for low temperature, old batteries and very low SOC. For example, for a set of well-balanced battery packs, when the SOC is relatively high, the SOC difference between them may be very small, such as 1-2%. But when the SOC is very low, the voltage of a certain cell will drop rapidly. The voltage of this cell is even more than 1V lower than other battery voltages. To ensure that the voltage of each cell is never lower than the minimum voltage given by the battery supplier, the SOP must accurately estimate the maximum output power of the cell whose voltage drops rapidly at the next moment to limit the use of the battery and protect the battery. The core of estimating SOP is to estimate each equivalent impedance of the battery online in real time.

　　SOH refers to the battery's state of health. It consists of two parts: ampere-hour capacity and power changes. It is generally believed that when the ampere-hour capacity decreases by 20% or the output power decreases by 25%, the battery life has expired. However, this does not mean that the car cannot be driven. For pure electric vehicles EV, the estimation of ampere-hour capacity is more important because it is directly related to the cruising range, while the power limit is only important at low SOC. For HEV or PHEV, the change in power is more important. This is because the battery's ampere-hour capacity is relatively small and the power it can provide is limited, especially at low temperatures. The requirements for SOH also require both high accuracy and robustness. And SOH without robustness is meaningless. If the accuracy is less than 20%, it is meaningless. The estimation of SOH is also based on the estimation of SOC. Therefore, the SOC algorithm is the core of the algorithm. The battery status estimation algorithm is the core of BMS. Everything else is in service of this algorithm. So when someone claims to have broken through or mastered the core technology of BMS, you should ask him what exactly he has done in BMS? Is it an algorithm, active balancing, or just BMS hardware and underlying software? Or just propose a structural way of BMS?

　　Some people say that Tesla is awesome because its BMS can manage 7104 batteries. Is this where it’s awesome? Is it really managing 7104 batteries? The Tesla model S does use 7104 batteries, but only 96 are connected in series, and those connected in parallel can only be counted as one battery, no matter how many cells you connect in parallel. Why? Because other companies' battery packs only count the number of series connections rather than the number of parallel connections. Why should Tesla be special? In fact, if you understand Tesla’s algorithm, you will know that Tesla’s algorithm not only requires a large amount of working condition data for calibration, but also cannot guarantee the estimation accuracy under any circumstances, especially after the battery ages. Of course, Tesla's algorithm is still much better than almost all domestic BMS algorithms. Domestic BMS algorithms are almost all current integral plus open circuit voltage methods. The open circuit voltage is used to calculate the initial SOC, and then the current integral is used to calculate the change in SOC. The problem is that if the voltage at the starting point is wrong, or the ampere-hour capacity is inaccurate, wouldn't it be possible to correct the error until it is fully charged again? Will there be an error if the voltage at the starting point is wrong? Experience tells us that it will, although the probability is very low. If you want to be foolproof, you cannot just rely on the precise voltage at the starting point to ensure the correct starting SOC.

　　What is the balancing problem of China's new energy vehicles?

　　Last year, a certain active balancing technology that was selected by experts won the Golden Globe Award for a certain lithium battery. The reason is that its core technology, active balancing technology, can extend battery life by 30% and cruising range by 20%. This seems unreliable. Because it is simply impossible to quantify. Who can you compare with to extend your life span by 30%? Does it make sense to compare yourself to yourself? Compared to no equilibrium? Then your level is far behind. Comparing yourself with others should only be meaningful if you compare yourself with the best. None of the BMSs in the world that are at least decent, if not the best, have balance problems. How do you extend your life span by 30%? The same goes for extending the cruising range. For example, Chrysler's Fiat500e has a SOC limit of 5%. How can you extend the cruising range by 20%? Going one step further, is it difficult to actively balance? Hardware: In 2008, TI promoted its active balancing IC to the company I was working for at the time. The algorithm is nothing more than balancing the batteries from the same module and balancing the batteries between different modules. General Motors completed simulation verification 6-7 years ago. There are even articles. From an algorithmic perspective, there is no difficulty at all. And active balancing is not what the Internet says at all. The active balancing function has always been the trump card of foreign products. Why do foreign countries basically not use active balancing? Mainly due to cost issues. If passive equalization can be done, why use active equalization? Why does China strongly advocate active balance? The author believes that the main reason is that passive equilibrium cannot be achieved. Speaking of passive balancing, most people told me that it is because the quality of domestic batteries is too poor and the consistency is poor. However, through conversations, the author found that the root cause lies in unclear concepts and incorrect methods. Otherwise, why would the balance become worse and worse when driving? The effect of equalization can be calculated. The so-called multiple equilibrium technology clearly means that there is no one way to achieve equilibrium. Some people say that passive equalization wastes a lot of electricity. So not good. Taking a 96-cell battery pack in series as an example, we can calculate how much power is wasted by passive balancing in the worst case. If the balancing current is 0.1A, a battery will waste approximately 0.4W when being balanced. The worst case is that 95 batteries need to be discharged, so the worst case is 0.4X95=38W. Not as expensive as a car headlight (about 45 watts). If it's not the worst case scenario, maybe only a dozen watts or even a few watts is enough. So, although passive equalization wastes a little power, if it can greatly extend the life of the battery, why not? Others say that the 0.1A current is too small for batteries with relatively large ampere-hour capacity. If imbalance can be nipped in the bud, there will be no powerlessness. If the battery core itself is no longer working properly, neither active balancing nor passive balancing can do anything. So, the poor consistency of the battery cannot be entirely blamed. You also need to find the reasons within yourself. There are two PHEV cars in the car that the author has built. The SOC in the battery pack differed by as much as 45% after driving for only a few months. Moreover, due to problems with SOC and SOP, cars often break down on the road. The company unanimously believed that it was a battery quality problem and unanimously agreed to change the battery supplier. But I just changed the algorithm and solved the equilibrium problem. And it was done under the company's clear regulations that charging is not allowed. Because a car has been involved in an accident due to battery problems. The difference in cell SOC in the battery pack has been reduced from 45% to 3%. The car has now traveled hundreds of thousands of kilometers. The problem of breaking down never happened again.

　　What kind of algorithm is considered core technology?

　　From a control perspective, a good algorithm should have two criteria: accuracy and robustness (error correction ability). The higher the accuracy, the better. I won’t go into detail here. The aforementioned current integral plus open-circuit voltage actually uses the open-circuit voltage for error correction, but this method is obviously far less robust than online real-time error correction. This is the reason why large foreign companies are using online real-time estimation of open circuit voltage to achieve online real-time error correction.

　　Why is there an emphasis on real-time online estimation here? What are its benefits? All equivalent parameters of the battery are estimated through real-time online estimation, thereby accurately estimating the status of the battery pack. Real-time online estimation greatly simplifies battery calibration work. This makes precise control of battery pack status with poor consistency a reality. Real-time online estimation enables high accuracy (Accuracy) and strong error correction capability (Robustness or error correction capability) whether it is a new battery or an aging battery.

　　Some people in China often don’t know what other people’s algorithms are. They think that they have mastered the core technology of BMS when they see that a certain manufacturer produces certain parts of BMS for a certain factory. This is not appropriate. Those large publications that cost tens of thousands of dollars to buy comment on the pros and cons of BMS from various manufacturers, but do not care about the differences in algorithms or core technologies of each BMS. The actual significance is too small. Just looking at whether it provides a BMS for a well-known OEM will make you think it is awesome, and you don’t know what exactly it provides in the BMS. I don’t know if there is a mentality of admiring foreign things.

　　What characteristics should the best BMS in the world currently have? It can estimate the battery parameters of the battery pack online in real time to accurately estimate the SOC, SOP, and SOH of the battery pack, and can correct the initial SOC error exceeding 10% and the ampere-hour capacity error exceeding 20% or percentage in a short time. A few percent of the current measurement error. When General Motors of the United States was developing the Volt 6 years ago, it conducted an experiment to test the robustness of the algorithm: Remove one string from a battery pack of 3 series connected in parallel. At this time, the internal resistance increases by 1/3 and the ampere resistance increases by 1/3. The capacity is reduced by 1/3. But BMS doesn't know. The result is that SOC and SOP are all corrected in less than 1 minute and SOH is then accurately estimated. This not only demonstrates the powerful error correction capabilities of the algorithm, but also shows that the algorithm can maintain estimation accuracy throughout the battery's entire life cycle.

　　For computers, if a blue screen appears, we generally only need to restart the computer. However, for cars, even if the probability of breaking down is only one in ten thousand, it is intolerable. So, unlike publishing articles, automotive electronics need to be guaranteed to work under any circumstances. Making a good algorithm requires a lot of energy to solve situations where the probability of occurrence is only one in a thousand or one in ten thousand. Only in this way can everything be guaranteed. For example, when a car is driving on a winding mountain road at high speed, everyone knows that the battery model will fail. This is because continuous high current will quickly consume the charged ions on the electrode surface, and the internal ions will not have time to diffuse out, and the battery voltage will drop sharply. The estimated SOC will have a large error, even an error of more than 10%. The precise mathematical model is the diffusion equation taught in mathematical physics textbooks. However, it cannot be used in cars because the numerical solution is too computationally intensive. The CPU computing power of the BMS is insufficient. This is not only an engineering problem, but also a mathematical and physical one. Solving such technical difficulties can resolve almost all known polarization problems that affect battery state estimation.

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