In recent years, energy and environmental issues have become more and more prominent, and electric vehicles powered by lithium-ion battery have shown great potential and advantages in alleviating these issues. Compared with other batteries, lithium-ion batteries have the advantages of high specific energy, high energy density, long endurance, low self-discharge and long shelf life. However, temperature of the battery has become one of the most important parameters to be handled properly for the development and propagation of lithium-ion battery electric vehicles. Both the higher and lower temperature environments will seriously affect the battery capacity and the service life. Under high temperature environment, lithium-ion batteries may produce thermal runaway, resulting in short circuit, combustion, explosion and other safety problems. Lithium dendrites may appear in lithium-ion batteries at low temperature, causing short circuit, failure to start and other operational faults. In this paper, the used thermal management methods of lithium-ion batteries are introduced and their advantages and disadvantages are discussed and compared. At the same time, the prospect of future development is put forward.

SUMMARYCoulomb counting method is a convenient and straightforward approach for estimating the state-of-charge (SOC) of lithium-ion batteries. Without interrupting the power supply, the remaining capacities of them in an electric vehicle (EV) can be calculated by integrating the current leaving and entering the batteries. The main drawbacks of this method are the cumulative errors and the time-varying coulombic efficiency, which always lead to inaccurate estimations. To deal with this problem, a least-squares based coulomb counting method is proposed. With the proposed method, the coulombic losses can be compensated by charging/discharging coulombic efficiency η and the measurement drift can be amended with a morbid efficiency matrix. The experimental results demonstrated that the proposed method is effective and convenient.

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The latest edition of the Highway Capacity Manual (HCM-6) includes, for the first time, a methodology for estimating and predicting the average travel time distribution (TTD) of urban streets. Travel time reliability (TTR) metrics can then be estimated from the TTD. The HCM-6 explicitly considers five key sources of travel time variability. A literature search showed no evidence that the HCM-6 TTR model has ever been calibrated with empirical travel time data. More importantly, previous research showed that the HCM-6 underestimated the empirical TTD variability by 70% on a testbed in Lincoln, Nebraska. In other words, the HCM-6 TTR metrics reflected a more reliable roadway than would be supported by field measurements. This paper proposes a methodology for calibrating the HCM-6 TTR model so that it better estimates the empirical TTD. This calibration approach was used on an arterial roadway in Lincoln, Nebraska, and no statistically significant differences were found between the calibrated HCM-6 TTD and the empirical TTD at the 5% significance level.

Figure 13. A) The chemical structure and multifunctional synergy mechanism of the biomimetic bilayer MFPHs actuators containing the pHresponsive AIEgen tetra-(4-pyridylphenyl)ethylene (TPE-4Py). B) Photographs of the flower-shaped bilayer hydrogel actuatord isplaying simultaneous fluorescence color,brightness, and shape-changing behavior in an aqueouss olution at pH 3.12. Reproducedf rom Ref. [18] with permission.

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