This paper presents a method for predicting the driving range of an e-mobility on a single charge. In the development of innovative e-mobility solutions, the range attainable on a single charge serves as a critical performance indicator. The driving range is significantly related to the battery system of the e-mobility. Accurate predictions of the driving range can shorten the battery design process and reduce costs in the development of battery systems. A longitudinal dynamics model of the vehicle is introduced to predict the single-charge driving range of the e-mobility. Within the driving cycle, the output exerted by the motor is calculated, as well as the energy consumed by the battery. Prediction of the decrease in the state-of-charge of the battery pack during driving is used for estimating the driving range. The proposed method is validated through MATLAB/Simulink-based simulations and experiments, showing an error rate of around 1% in the driving distance of e-mobility.

In this paper, we propose an adaptive safety distance that is adjusted along the uncertain braking duration of the object vehicle resulting in an improvement of driving comfort. In the real world, the object vehicle decelerates for uncertain duration, while the conventional strategies assume that the object vehicle decelerates until full stop. By imposing a constraint on the ego vehicle to stop simultaneously with the object vehicle, the driving comfort is enhanced by activating full braking (FB) only when it is necessary. To accomplish these, two concepts are proposed; effective collision avoidance (ECA) condition and full braking activation parameter (FBAP). ECA refers to a strategy in which the ego vehicle stops simultaneously with the object vehicle to account for its uncertain deceleration duration. FBAP is suggested to determine when to activate FB by adjusting the duration of partial braking (PB). Virtual experiments are conducted strictly with various scenarios to validate the performance of the proposed FBAP-based safety distance. The test results demonstrate that the suggested FBAP-based safety distance is applicable to a wide range of driving speeds, improving driving comfort and performing collision avoidance compared to conventional methods.

Recently, legged robots have been used for various purposes, such as exploring unknown terrain or interacting with the world. For control and planning legged systems during interactive operations, it is essential to estimate and respond to external forces. However, in legged system, it becomes difficult to estimate forces due to highly dynamic situations. There are several studies that use a force sensor on the foot and end effector, but these approaches have disadvantages in terms of cost and sustainability. Therefore, in this paper, we propose an improved method for estimating external forces without a force sensor. First, each leg force was obtained using the system dynamics of the robot with a disturbance observer. Then, by preintegration, it was tightly coupled with other sensors to estimate the pose and external force simultaneously. Despite the impact and slip, we estimate external forces accurately in standing and walking motions. Moreover, we compared pose estimation performance with VINS-Mono [1], and there is no significant accuracy degradation in spite of highly dynamic force residual.