Abstract Autonomous Vehicles (AVs) have shown indelible and revolutionary effects on
accident reduction and more efficient use of travel time, with outstanding socio‐economic …

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

This paper proposes a real-time predictive energy management strategy (PEMS) of plug-in
hybrid electric vehicles for coordination control of fuel economy and battery lifetime …

The application of machine learning-based state-of-health (SOH) prediction is hindered by
the large demand for training data. To conquer this defect, a flexible and easily transferred …

A supervisory control strategy, including dynamic control supervisor, handling-stability
controller, energy efficiency controller, and coordinated torque allocator, is proposed for …

Accurate estimation of the state of charge (SOC) of lithium-ion battery packs remains
challenging due to inconsistencies among battery cells. To achieve precise SOC estimation …

The expansion of electric vehicles in urban areas has paved the way toward the era of
autonomous vehicles, improving the performance in smart cities and upgrading related …

This article proposes a predictive energy management strategy of plug-in hybrid electric
vehicles by real-time optimization and data-driven calibration. The powertrain modelling and …

To enhance the active safety performance for automated electric vehicles (AEVs) at driving
limits, the collaborative control of four-wheel steering (4WS) and direct yaw-moment control …

Abstract Model predictive control (MPC) is widely used in the motion control of autonomous
vehicles. However, the conventional MPC relies on an accurate model and cannot achieve …