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In the field of active safety, the active four-wheel-steering (4WS) system seems to be an attractive alternative and an effective tool to improve the vehicles' handling stability in lane-keeping control performance. Under normal using condition, the vehicle's lateral acceleration is comparatively small, and the mathematic relationship between the small side force excitation and the small slip angle of the tire is in the linear region. Furthermore, the effects of roll, heave, and pitch motions are neglected as well as the dynamic characteristics of the tires and suspension system in this work. Therefore, the linear quadratic control (LQC) theory is used to ensure that the output of the 4WS control system can keep track of the desired yaw rate and zero-sideslip-angle response can also be realized at the same time.

The automobile exhaust energy can be recovered by the thermoelectric module generator(TEG). Owing to the complex urban traffic, the exhaust gas’s temperature fluctuations are resulted, which means the unstable hot-end temperature of the TEG. By installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, it is possible to appropriately reduce the temperature fluctuation, but there is still a fluctuation of the TEG’s power output. Then by adding voltage filter circuit (VFC) after the TEG, the power output stability can be improved. This research uses SHCM and VFC to improve the stability of the exhaust gas generation. Firstly, the three-dimensional heat transfer model of the exhaust pipe thermoelectric power generation system is established. The heat capacity materials with low thermal resistance and high heat capacity were selected as the research object based on previous research.

In order to solve the environmental pollution and energy crisis, Electric Vehicles (EVs) have been developed rapidly. Lithium-ion (Li-ion) battery is the key power supply equipment for EVs, and the scientific and accurate prediction of its Remaining Useful Life (RUL) has become a hot topic in the field of new energy research. The internal resistance and capacity are often used to characterize the Li-ion battery State of Health (SOH) from which RUL is obtained. However, in practical applications, it is difficult to obtain internal resistance and capacity information by using the non-intrusive measurement method. Therefore, it is necessary to extract the measurable parameters to characterize the degradation of Li-ion battery. At present, the methods of extracting health indicators based on measurable parameters have gained preliminary results, but most of them are derived from the Li-ion battery discharging data.