The temperature of electric vehicle batteries needs to be controlled through a thermal management system to ensure working performance, service life, and safety. In this paper, TAFEL-LAE895 100Ah ternary Li-ion batteries were used, and discharging experiments at different rates were conducted to study the surface temperature increasing characteristics of the battery. To dissipate heat, heat pipes with high thermal conductivity were used to accelerate dissipating heat on the surface of the battery. We found that the heat pipe was sufficient to keep the battery temperature within the desired range with a midlevel discharge rate. For further improvement, an additional thermoelectric cooler was needed for a high discharge rate. Simulations were completed with a battery management system based on a heat pipe and with a combined heat pipe and thermoelectric cooler, and the results were in line with the experimental results. The findings show that the combined system can effectively reduce the surface temperature of a battery within the full range of discharge rates expected in the battery used.

Scientific and reasonable battery thermal management systems contribute to improve the performance of a power battery, prolong its life of service, and improve its safety. Based on TAFEL-LAE895 type 100Ah ternary lithium ion power battery, this paper is conducted on charging and discharging experiments at different rates to study the rise of temperature and the uniformity of the battery. Paraffin can be used to reduce the surface temperature of the battery, while expanded graphite (EG) is added to improve the thermal conductivity and viscosity of the composite phase change material (CPCM), and to reduce the fluidity after melting. With the increase of graphite content, the heat storage capacity of phase change material (PCM) decreases, which affects the thermal management effect directly. Therefore, this paper combines heat pipe and semiconductor refrigeration technology to transform heat from the inner CPCM to the thermoelectric cooling sheet for heat dissipation. The results show that the surface temperature of the battery can be kept within a reasonable range when discharging at high rate. The temperature uniformity of the battery is improved and the energy of the battery is saved.

As is known to all, a battery pack is significantly important for electric vehicles. However, its performance is easily affected by temperature. In order to address this problem, an enhanced battery thermal management system is proposed, which includes two parts: a modified cooling structure and a control unit. In this paper, more attention has been paid to the structure part. According to the heat generation mechanism of a battery and a thermoelectric chip, a simplified heat generation model for a single cell and a special cooling model were created in ANSYS 17.0. The effects of inlet velocity on the performance of different heat exchanger structures were studied. The results show that the U loop structure is more reasonable and the flow field distribution is the most uniform at the inlet velocity of 1.0 m/s. Then, on the basis of the above heat exchanger and the liquid flow velocity, the cooling effect of the improved battery temperature adjustment structure and the traditional liquid temperature regulating structure were analyzed. It can be seen that the liquid cooling structure combined with thermoelectric cooling demonstrates a better performance. With respect to the control system, the corresponding hardware and software were also developed. In general, the design process for this enhanced battery thermal management system can provide a wealth of guidelines for solving similar problems. The H commutation circuit, matrix switch circuit, temperature measurement circuit, and wireless communication modules were designed in the control system and the temperature control strategy was also developed.

Accurately estimating the state of charge (SOC) of power batteries in electric vehicles is of great significance to the measurement of the endurance mileage of electric vehicles, as well as the safety protection of the power battery. In view of lithium ion batteries’ nonlinear relation between SOC estimation and current, voltage, and temperature, the improved Back Propagation (BP) neural network method is proposed to accurately estimate the SOC of power batteries. To address the inherent limitations of BP neural network, particle swarm algorithm is adopted to modify the relevant weighting coefficients. In this paper, the lithium iron phosphate battery (3.2 V/20 Amper-Hour) was studied. Charge and discharge experiments were conducted under a constant temperature. The training data were used to construct the surrogate model using the improved BP neural network. It is noted that the accuracy of the developed algorithm is increased by 2% as compared to that of conventional BP. Finally, an actual vehicle condition experiment was designed to further verify the accuracy of these two algorithms. The experimental results show that the improved algorithm is more suitable for real vehicle operating conditions than the traditional algorithm, and the estimation accuracy can meet the industry standards to a greater extent.

A multifunctional aviation aluminum alloy with good superhydrophobicity and corrosion resistance was prepared by a two-step process of etching followed by polymer modification. Meanwhile, micro- and nanostructures formed on the processed sample. Compared with bare sample, the static liquid contact angle on the as-prepared sample was increased by 100.8°. Further polarization tests showed that the corrosion potential of such a sample increased, and the corrosion current density decreased obviously, thus suggesting that the corrosion resistance of the modified sample was significantly improved. The same conclusion was confirmed by subsequent impedance testing. The work is of great economic value and practical significance to enhance the corrosion resistance of aviation actuator materials and also lays a foundation for future hydrophobic application research in aeronautical engineering.

For the laser tracking and positioning system of a moving target using a four-quadrant detector, the accuracy of laser spot position detection has a serious impact on the tracking performance of the system. For moving target tracking, the traditional spot position detection method of a four-quadrant detector cannot give better consideration to both detection accuracy and operation speed. In view of this, an improved method based on piecewise low-order polynomial least squares fitting and a Kalman filter is proposed. Firstly, the tracking and positioning mathematical model of the system is created, and the experimental device is established. Then, the shortcomings of traditional methods are analyzed, and the improved method and the real-time tracking and positioning algorithm of the system are studied. Finally, through the experiment, the system operation effects are compared and analyzed before and after the improvement. The experimental results of system dynamic tracking show that, the least squares fitting of the experimental data using a 5-segment and quadratic polynomial can achieve better results. By using the improved method, the maximum tracking distance of a moving object is increased from 12 m to more than 30 m. At a distance of 7.5 m, the maximum tracking speed can reach 2.11 m/s, and the root mean square error (RMSE) of the position is less than 4.59 mm. At 15.5 m, the maximum tracking speed is 2.04 m/s and the RMSE is less than 5.42 mm. Additionally, at 23.5 m, it is 1.13 m/s and 5.71 mm.