Recently, vehicle platooning has attracted a lot of attention as one of the promising solutions to the explosion of vehicle numbers. By exchanging information among vehicles through communication networks, vehicle platooning can significantly improve traffic safety and efficiency. In this paper, we develop a joint systematic design of platoon communication and control to reduce position errors of consecutive vehicles and to improve platoon safety. Through separate information dissemination of the platoon leader and followers, we improve the success probability of the platoon leader's information dissemination. To extend the communication range of the platoon leader and also the platoon scale, we propose to use relays to forward the platoon leader's messages. Further, an adaptive distributed model predictive control (DMPC) based controller is presented, which can adjust its control parameters according to platoon state and dynamic information sources. Simulation results not only verify the proposed systematic design in terms of position errors, but also show that our scheme performs well in vehicle failure cases where collisions can be avoided and platoon safety improved.

The aging of lithium-ion batteries (LIBs) is a crucial issue and must be investigated. The aging rate of LIBs depends not only on the material and electrochemical performance but also on the working conditions. In order to assess the impact of vehicle driving conditions, including the driving cycle, ambient temperature, charging mode, and trip distance on the battery life cycle, this paper first establishes an electric vehicle (EV) energy flow model to solve the operating parameters of the battery pack while working. Then, a powertrain test is carried out to verify the simulation model. Based on the simulated data under different conditions, the battery capacity fade process is estimated by using a semi-empirical aging model. The mileage (Ф) traveled by the vehicle before the end of life (EOL) of the battery pack is then calculated and taken as the evaluation index. The results indicate that the Ф is higher when the vehicle drives the Japanese chassis dynamometer test cycle JC08 than in the New European Driving Cycle (NEDC) and the Federal Test Procedure (FTP-75). The Ф will be dramatically reduced at both low and high ambient temperatures. Fast charging can increase the Ф at low ambient temperatures, whereas long trip driving can always increase Ф to varying degrees.

Adaptive unscented Kalman filter (AUKF) has been widely used for state of charge (SOC) estimation of lithium‐ion battery. The noise covariance of the conventional AUKF method is updated based on the innovation covariance matrix (ICM), which is estimated using the error innovation sequence (EIS). However, the distribution of EIS changes due to the time‐varying noise, load current dynamics and modelling error, which will lead to inaccurate ICM estimation. Therefore, an intelligent adaptive unscented Kalman filter (IAUKF) method is proposed to detect the distribution change of EIS. Then, the ICM is estimated based on the EIS after the distribution change. Results show that the IAUKF method can improve SOC estimation accuracy significantly. Compared with that of the AUKF method, the root mean squared error and the mean absolute error of SOC based on the IAUKF method decrease by 43.70% and 72.37% under random walk discharge condition, respectively. In addition, the computation time of the IAUKF method slightly increases by 6.27% compared with that of AUKF method. Finally, the effect of initial parameters on the SOC estimation accuracy was analysed. The results indicate that proper algorithm tuning, such as initial window length of EIS for ICM update and the threshold value, can further improve the SOC accuracy based on the proposed IAUKF method. The proposed IAUKF method also shows high robustness against initial measurement noise covariance.

Lithium-ion battery heat generation characteristics during aging are crucial for the creation of thermal management solutions. The heat generation characteristics of 21700 (NCA) cylindrical lithium-ion batteries during aging were investigated using the mathematical model that was created in this study to couple electrochemical mechanisms, heat transfer, and aging loss. These findings indicate that, at the same operating current, the heat generation power of the cell increased significantly with battery aging. This increase was primarily due to the energy loss caused by the growth of the solid–electrolyte interface (SEI) and a reduction in the negative porosity and other physical characteristics of the SEI, such as its ionic conductivity and molar volume, which also had an impact on the heat generation power. By investigating the variations in battery heat generation in different aging modes, the electrochemical mechanisms underlying the effects of aging on battery heat generation can be comprehended in depth.

To evaluate the performance of newly designed electro-pneumatic valves (EPVs) for the air-powered engine (APE) and study laws of parameters affecting them, a simulation model was established based on the thermodynamics and mechanics theories. Experiments were set up to determine the instantaneous effective orifice area of solenoid valve by the constant volume discharge method. The simulation model was also validated by comparing the measured displacement curve with the simulated displacement curve of the valve in the pressure of 0.16 and 0.49 MPa. Simulation and experimental results showed that maximum working frequency of the designed EPV could reach 30 Hz corresponding to 2000 r/min of engine rotating speed. Based on simulation results, impacts of temperature and pressure of control air on delay time, full opening/closing time and seating velocity of EPV were analyzed. The simulation model could also act as EPV simulation prototype in designing the air exchange control system of APE.