Global warming is increasing at the alarming rate in the recent years. One of the best solutions to reduce the global warming is generation of power from the carbon neutral and negative technologies. In view of this, harvesting energy from the photosynthesis is one of the best viable solution. The Microphotosynthetic cell (μPSC), presented in this work, functions on the principle of photosynthesis and respiration. Typical power produced by a μPSC varies in the range of 0.1–10 mW. In this paper, we discussed the potential applications of the Microphotosynthetic power cells to the automotive sector and Autonomous Vehicles (AV).
Lane-changing is an important operation of an autonomous vehicle driving on the road. Safety and comfort are fully considered by excellent drivers in lane-changing operation. However, only the kinematic and dynamic constraints are taken into account in the traditional path planning methods, and the path generated by the traditional methods is very different from the actual trajectory of the vehicle driven by the excellent driver. In this paper, a path planning method for imitating the lane-changing operation of excellent drivers is proposed. Five experienced drivers are invited to do the lane-changing test, and the lane-changing trajectories data under different conditions are recorded. The excellent driver lane-changing model is established based on the genetic algorithm (GA) and back propagation (BP) neural network trained by the data of the lane-changing tests. The proposed approach can plan out an optimized lane change path according to the vehicle condition by learning the excellent drivers’ driving routes. The results of simulations verify that the path generated by the proposed algorithm is basically same as the track selected by the excellent drivers under same conditions, which can reflect the characteristics of the operations of the excellent driver. While applying safe lane-changing to autonomous vehicle, it can improve the ride comfort of the vehicle and therefore reduce the probability of motion sickness of the passengers caused by improper operation during lane change.
To solve the contradiction between handling stability and ride comfort of vehicles with interconnected air suspension system (IASS) and reduce the energy consumption of air suspension with adjustable spring stiffness, a coordinated control for dynamic performance was designed based on the logic of switching interconnection modes and game control for the damper. The control system consists of a switching controller for air suspension interconnection modes and a distribution controller for the damping force. The switching controller determines the optimal air suspension interconnection mode by calculating the vehicle dynamic performance index in real-time. The distribution controller achieves a distribution for optimal damping force based on an infinite time differential game. veDYNA software that is a vehicle dynamics analysis software based on MATLAB/Simulink was used to verify the algorithm, and the accuracy was verified by a bench test. Finally, the results show this coordinated system can significantly improve the ride comfort and restrain the pitching motion. Compared with traditional suspension, the vertical acceleration decreases by 18.32% and the dynamic stroke decreases by more than 10% under the straight condition; the vertical acceleration decreases by 12.24% and the roll angle decreases by 1.26% under the steering condition.
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