New non-destructive fast intelligent charger circuit diagram

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Overview:
The current fast charger cannot follow the characteristics of the battery itself for rapid charging, resulting in more gas evolution, large temperature rise, and shortened battery life. In response to the above problems, it is innovatively proposed to use ANFIS to predict the acceptable current of the battery to ensure that the battery is quickly and non-destructively charged at the optimum charging rate. Detailed introduction of the single-chip XC164CM as the core, complete the design of a new fast lossless intelligent charger, with current detection and control and other functions. The prototype test shows that the gassing process is less, the temperature rise is low, and the charging efficiency is high, which solves the contradiction between the charging rate and the battery life.

According to Mas's theorem, the battery is quickly and non-destructively charged. The charging current should be equal to or close to the current current acceptable to the battery to ensure the lowest gassing rate and reduce the damage to the battery during rapid charging. Recently, advanced intelligent control technology has been introduced into fast charging technology for stop charging control or charging mode selection, improving control accuracy and charging efficiency; but not considering the battery's own charging characteristics, lack of adaptive ability, can not track battery charging The characteristic is changed to dynamically adjust the charging current, resulting in a charging current greater than the current that the battery can accept, causing damage to the battery caused by excessive temperature rise. To this end, it is necessary to design a new type of smart charger that can safely, non-destructively and quickly charge the battery.

In-depth study of the fast charging theory, starting from the characteristics of nickel-cadmium batteries, innovatively proposed the introduction of adaptive fuzzy neural network (ANFIS) to predict the acceptable current of the battery under different state of charge, thereby adjusting the actual charging current; meanwhile, charging A negative pulse is added to depolarize. On this basis, a new type of fast lossless smart charger design scheme is proposed by using Infineon's single chip XC164CM and peripheral interface circuit.

1 Characteristics of charging process of nickel-cadmium battery The charging curve of single-cell nickel-cadmium battery is shown in Figure 1. The entire charging process can be roughly divided into four stages.

Figure 1 Charging characteristics of nickel-cadmium battery

When the terminal voltage of the battery reaches 1.2 V and reaches the A point, the discharge should be stopped immediately. If the discharge is too deep, the temperature rise will be large. During the charging process, the main charging phase is the AB segment, and more than 70% of the energy of the entire battery is charged at this stage, and the voltage rise rate is slow. At the same time, the electrochemical reaction in the AB segment is combined with hydrogen at a certain rate of oxygen, so that the temperature rise and gas pressure inside the battery are low. During this time, it is suitable to use a large current for rapid charging, but the charging current must be less than the acceptable current of the battery, otherwise a large amount of gas is generated, the charging efficiency is lowered, and the temperature rise is too high, so that the battery is damaged. In the BC segment, the terminal voltage rises rapidly, and the internal impedance of the battery increases, which is suitable for reducing the charging current. In the CD segment, it enters the stop-and-charge phase, paying attention to timely stop-and-charge detection and phase-by-phase, using small current pre-charging in the OA phase; when reaching point A, entering the fast charging phase, where high-current pulse intelligent charging is used; The small current is recharged and finally stopped to the CD segment for charge detection.

2 Fast non-destructive charging strategy The battery mentioned in the literature can be simply regarded as a super-barrier container. The charging process of the battery can be regarded as the charging process of an RC circuit. The time constant τ represents the speed of charging, which is equivalent to the horse. The attenuation ratio α in the curve is τ = 1 / α. The acceptable current of the battery during charging is only related to the initial current I0. When t=3τ, the battery can be charged.

The current is about I0/20; when charging to t=5Ï„, the acceptable current of the battery is already small.

Thus, it is proposed to predict the acceptable current of the battery using the adaptive fuzzy neural network ANFIS. During the rapid charging process of the battery, the acceptable current is predicted according to the state of charge of the battery, and the charging current is ensured to meet the optimal charging curve of Mas, the gassing rate is low, and the battery is not damaged. The basic idea of ​​ANFIS predicting the acceptable current of the battery is: during the charging process, dynamically detecting the state parameter of the battery as the input of the ANFIS prediction model, and obtaining the current acceptable current ick by fuzzy reasoning, when the error between the predicted value ick and the expected value icp When the requirements are not met, the adaptive fuzzy controller generates a control response, adaptively corrects the output result of the hidden layer through the self-learning ability of the neural network, updates the connection weight between the layers, optimizes the fuzzy parameters, and recalculates the output. As a result, the prediction result is output until the error satisfies the requirement, thereby changing the current charging current so that the actual charging current is always approaching or equal to the acceptable current. At the same time, the introduction of negative pulse charging eliminates the polarization effect.
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