Search

The differential drive assist steering (DDAS) system improves the handiness of steering by torque difference between two-side wheels. However, the DDAS and the vehicle stability control (VSC) will interfere with each other due to the same actuators. This paper proposes a hierarchical coordination control approach for the DDAS and VSC. The system is divided into four layers: the parameter estimation layer, the control region division layer, the coordination decision layer, and the control allocation layer. In the control region division layer, the stable area is firstly determined on the $\beta - \dot{\beta }$ phase portrait, and the coordinated control region is obtained by applying the simulated annealing algorithm inwardly and outwardly to the boundary of the stable area. In the coordination decision layer, the direct control strategy of steering hand wheel torque is used to establish the controller of the DDAS based on the fuzzy adaptive PID algorithm. At the same time, the controller of yaw moment is established based on the sliding mode control theory. In the stable region, the DDAS works separately. The VSC works separately in the unstable region. In the coordination region, the Sigmoid function is used to adjust the weight coefficient of the DDAS dynamically. Besides, the control allocation layer includes torque distribution controller and vehicle slip ratio controller. Finally, the vehicle model is established in CarSim, the control strategy, and the wheel motor model are established in Simulink. The joint simulation results of several typical conditions show that the designed control strategy can improve the handling stability of the vehicle effectively while DDAS working even in severe driving condition. [ABSTRACT FROM AUTHOR]

Heavy-duty electric powertrains provide a potential solution to the high emissions and low fuel economy of trucks, buses, and other heavy-duty vehicles. However, the cost, weight, and lifespan of electric vehicle batteries limit the implementation of such vehicles. This paper proposes supplementing the battery with on-board photovoltaic modules. In this paper, a bus model is created to analyze the impact of on-board photovoltaics on electric bus range and battery lifespan. Photovoltaic systems that cover the bus roof and bus sides are considered. The bus model is simulated on a suburban bus drive cycle on a bus route in Davis, CA, USA for a representative sample of yearly weather conditions. Roof-mounted panels increased vehicle driving range by 4.7% on average annually, while roof and side modules together increased driving range by 8.9%. However, variations in weather conditions meant that this additional range was not reliably available. For constant vehicle range, rooftop photovoltaic modules extended battery cycle life by up to 10% while modules on both the roof and sides extended battery cycle life by up to 19%. Although side-mounted photovoltaics increased cycle life and range, they were less weight- and cost-effective compared to the roof-mounted panels. [ABSTRACT FROM AUTHOR]

Hybrid and electric vehicle batteries deteriorate from use due to irreversible internal chemical and mechanical changes, resulting in decreased capacity and efficiency of the energy storage system. This article investigates the modeling and control of a lithium-ion battery and ultracapacitor hybrid energy storage system for an electric vehicle for improved battery lifespan and energy consumption. By developing a control-oriented aging model for the energy storage components and integrating the aging models into an energy management system, the trade-off between battery degradation and energy consumption can be minimized. This article produces an optimal aging-aware energy management strategy that controls both battery and ultracapacitor aging and compares these results to strategies that control only battery aging, strategies that control battery aging factors but not aging itself, and non-optimal benchmark strategies. A case study on an electric bus with variously-sized hybrid energy storage systems shows that a strategy designed to control battery aging, ultracapacitor aging, and energy losses simultaneously can achieve a 28.2% increase to battery lifespan while requiring only a 7.0% decrease in fuel economy. [ABSTRACT FROM AUTHOR]