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Recovering the braking energy and reusing it can significantly improve the fuel economy of hybrid electric vehicles (HEVs).The battery ability of recovering electricity limits the improvement of the regenerative braking performance. As one way to solve this problem, the technology of brake-by-wire can be adopted in the HEVs to use the recovery dynamically. The use of high-power electrical equipment, such as electromechanical brake (EMB), is working in the form of brake-by-wire. Due to the nature of EMB, there exists an obvious coupling relationship between the energy flow and brake force distribution. In this paper, a brake force distribution controller is proposed in HEV with EMB, which can maximize braking energy recovery, compared with the conventional distribution control without EMB. Meanwhile, an energy flow strategy working with the distribution controller is designed, which is less limited to the performance of the battery.

In recent years, research on car-like robots has received more attention due to the rapid development of artificial intelligence from diverse disciplines. As essential parts, path planning and lateral path tracking control are the basis for car-like robots to complete automation tasks. Based on the two-degree-of-freedom vehicle dynamic model, this study profoundly analyzes the car-like robots’ path planning and lateral path tracking control. Three objectives: path length, path smoothness, and path safety, are defined and used to construct a multi-objective path planning model. By introducing an adaptive factor, redefining the selection of reference points, and using the cubic spline interpolation for path determination, an improved NGSA-III is proposed, which is mostly adapted in solving the multi-objective path planning problem.