Search Results

As electric vehicles become more widespread, such vehicles may be subject to “range anxiety” due to the risk of discharging during driving or the discharging when left unused for a long period. Accordingly, a vehicle equipped with a mobile charger that can provide a charge in an emergency. The vehicle with the mobile charger is usually composed of a large capacity battery, a power converter in a small truck. However, the large capacity battery and the power converter are disadvantageous in that they are large in size and expensive and should be produced as a special vehicle. In this paper, we propose a method to solve the problem using an internal EV system without requiring an additional power generation, battery and a charging-and-discharging device. The method is a novel Vehicle-to-Vehicle (V2V) fast charging control system utilizing motor and inverter in EV.

A practical application of the Target Cascading scheme for the development of the front bumper system of a passenger car is investigated in this paper. The Target cascading in the crash performance of vehicle developments requires a systematic approach, propagating from the desired vehicle-level performance target to appropriate specifications in a system- and/or component-level. To define the values of design specification in the front bumper system, three physical variables are derived by analyzing the vehicle-level performance of the frontal impact under the high-speed (56kph NCAP frontal impact) and the low-speed (15kph RCAR structural test) crash conditions. To ensure the sequential deformation in the high-speed frontal impact and to minimize the damage of the structural member in the low-speed crash, the maximum collapse load of a crash box should be smaller than the collapse load of a front side member.

This paper is concerned with the energy management strategy of hybrid electric vehicle using stochastic dynamic programming. The aim is the control strategy of the power distribution for hybrid electric vehicle powertrains to minimize fuel consumption while maintaining drivability. The fuel economy of hybrid electric vehicle is strongly influenced by power management control strategy. Rule-based control strategy is popular strategy thanks to its effectiveness in real-time implementation, but rule should be designed and efficiency of entire drive trains is not optimized. Dynamic programming, one of optimization-based control strategy presents outstanding performance, but cannot be used as real-time control strategy directly, since its non-causal property and drawback that global optimal solution can only be obtained for specific driving cycle. In this paper, stochastic dynamic programming is applied to parallel hybrid electric vehicle to optimize vehicle performance in average sense.

The study presented in this paper proposes an integrated and automated chassis design process, in which the associated design and analysis, including kinematic design and controller calibration, are sequentially performed through three steps. The first step is an automated kinematic design process that optimizes the hardpoints' coordinates and bush properties. First, ADAMS/Car is employed to evaluate the K&C characteristics by varying arrangements of the hardpoints and bush properties. In addition, a bush stiffness curve is approximated and represented by four parameters, allowing a designer to incorporate the curve as the design variables in the optimization process. Second, an optimization process is employed to automate the calibration of the UCC system modeled by Simulink, which is essential in improving the vehicle's dynamic behavior.