A Predictive Energy Management Strategy for Multi-Energy Source Vehicles Based on Full-Factor Trip Information

To achieve the real-time application of a dynamic programming (DP) control strategy, we propose a predictive energy management strategy (PEMS) based on full-factor trip information, including vehicle speed, slip ratio and slope. Firstly, the prediction model of the full-factor trip information is proposed, which provides an information basis for global optimization energy management. To improve the prediction’s accuracy, the vehicle speed is predicted based on the state transition probability matrix generated in the same driving scene. The characteristic parameters are extracted by a feature selection method taken as the basis for the driving condition’s identification. Similar to speed prediction, regarding the uncertain route at an intersection, the slope prediction is modelled as a Markov model. On the basis of the predicted speed and the identified maximum adhesion coefficient, the slip ratio is predicted based on a neural network. Then, a predictive energy management strategy is developed based on the predictive full-factor trip information. According to the statistical rules of DP results under multiple standard driving cycles, the reference SOC trajectory is generated to ensure global sub-optimality, which determines the feasible state domain at each prediction horizon. Simulations are performed under different types of driving conditions (Urban Dynamometer Driving Schedule, UDDS and World Light Vehicle Test Cycle, WLTC) to verify the effectiveness of the proposed strategy.

Actor-Critic Traction Control Based on Reinforcement Learning with Open-Loop Training

The use of actor-critic algorithms can improve the controllers currently implemented in automotive applications. This method combines reinforcement learning (RL) and neural networks to achieve the possibility of controlling nonlinear systems with real-time capabilities. Actor-critic algorithms were already applied with success in different controllers including autonomous driving, antilock braking system (ABS), and electronic stability control (ESC). However, in the current researches, virtual environments are implemented for the training process instead of using real plants to obtain the datasets. This limitation is given by trial and error methods implemented for the training process, which generates considerable risks in case the controller directly acts on the real plant. In this way, the present research proposes and evaluates an open-loop training process, which permits the data acquisition without the control interaction and an open-loop training of the neural networks. The performance of the trained controllers is evaluated by a design of experiments (DOE) to understand how it is affected by the generated dataset. The results present a successful application of open-loop training architecture. The controller can maintain the slip ratio under adequate levels during maneuvers on different floors, including grounds that are not applied during the training process. The actor neural network is also able to identify the different floors and change the acceleration profile according to the characteristics of each ground.

Prescribed Performance Active Braking Control with Reference Adaptation for High-Speed Trains

Active braking control systems are vital for the safety of high-speed trains by leading the train operation at its maximum adhesion state. The train adhesion is a nonlinear function of the slip ratio and varies with the uncertain wheel-rail contact conditions. A nonlinear active braking control with rapid and accurate tracking performance is highly required for train braking systems. This paper proposes a novel prescribed performance active braking control with reference adaptation to obtain the maximum adhesion force. The developed feedback linearization controller employs a prescribed performance function that specifies the convergence rate, steady-state error, and maximum overshoot to ensure the transient and steady-state control performance. Furthermore, in the designed control approach, a continuous-time unscented Kalman filter is introduced to estimate the uncertainty of wheel-rail adhesion. The estimation is utilized to represent uncertainty and compensate for the prescribed performance control law. Finally, based on the estimated wheel-rail adhesion, an on-line optimal slip ratio generation algorithm is proposed for the adaptation of the reference wheel slip. The stability of the system is provided, and experiment results validate the effectiveness of the proposed method.

Static and Dynamic Analysis of Non-Pneumatic Tires Based on Experimental and Numerical Methods

Since the beginning of their production, pneumatic tires have experienced tremendous improvements in structure and materials, becoming the dominant design in the world tires market. Nevertheless, relying upon pressurized air, they are affected by maintenance and security issues that can lead to fatal accidents. Therefore, tire-makers are investigating new tire designs, called Airless or Non-Pneumatic, with the aim of removing air-related problems. The research about such tires is still at an early stage, especially if compared to the one conducted on the pneumatic ones. In this paper, the development of a methodology capable of studying the mechanical behavior of a Non-Pneumatic Tire (NPT) by means of experimental data and numerical approach is illustrated. The experimental activities consisted of a scanner acquisition of the NPT and a footprint analysis for the calculation of the radial stiffness and contact patch pressure distribution. Moreover, the Digital Image Correlation (DIC) technique was applied to carry out a more specific study about the spoke’s deformation. From the acquired 3D model, a calculation of the NPT vertical deflection with finite element analysis (FEA) was performed—validating the model and then submitting it to a steady state analysis—that allows the simulation of a steady state rolling tire with the possibility to replicate different values of slip ratio. The results of the experimental activities are in good agreement with the ones obtained with FEA, further validating the developed methodology.

Theoretical Tire Model for Wear Progress of Tires with Tread Pattern Considering Two-Dimensional Contact Patch

ABSTRACT A new theoretical tire model for the wear progress of tires with tread block pattern is developed considering a two-dimensional contact patch. In the model, the wear energy is calculated from the shear force and pressure distribution in a two-dimensional contact patch that are changed with not only shear forces in a contact patch but also with the wear and irregular wear of tires. The fore–aft shear force in a contact patch consists of six mechanisms related to slip ratio, camber, contact between a tire and a road, barrel deformation of a loaded block, rolling resistance, and a rolling tire with rounded crown shape, whereas the lateral shear force consists of three mechanisms related to slip angle/camber, contact of a tire with rounded crown shape, and barrel deformation of a loaded block. The heel and toe irregular wear and the progress of irregular wear under pure slip condition qualitatively agree with the conventional knowledge of tire engineers. The expected wear energy is introduced to predict the wear progress under combined slip condition in the wear course. Using the vehicle dynamics to predict the tire force history, a histogram of external forces is obtained by transforming from it. Calculating wear energies by changing slip angle and slip ratio, the relation between external forces and the wear energy is expressed as the response surface. Multiplying the wear energy by the histogram, the expected wear energy distribution in a block is calculated. Assuming that the worn depth is proportional to the expected wear energy, the wear progress is predicted.

Localization and Surface Characterization by Zhurong Mars Rover at Utopia Planitia

China’s first Mars rover, Zhurong, has successfully touched down on the southern Utopia Planitia of Mars at 109.925° E, 25.066° N, and since performed cooperative multiscale investigations with the Tianwen-1 orbiter. Here we present primary localization and surface characterization results based on complementary data of the first 60 sols. The Zhurong rover has traversed 450.9 m southwards over a flat surface with mild wheel slippage (less than 0.2 in slip ratio). The encountered crescent-shaped sand dune indicates a NE-SW local wind direction, consistent with larger-range remote-sensing observations. Soil parameter analysis based on terramechanics indicates that the topsoil has high bearing strength and cohesion, and its equivalent stiffness and internal friction angle are ~1390-5872 kPa∙m-n and ~21°-34° respectively. Rocks observed strewn with dense pits, or showing layered and flaky structures, are presumed to be involved in physical weathering like severe wind erosion and potential chemical weathering processes. These preliminary observations suggest great potential of in-situ investigations by the scientific payload suite of the Zhurong rover in obtaining new clues of the region’s aeolian and aqueous history. Cooperative investigations using the related payloads on both the rover and the obiter could peek into the habitability evolution of the northern lowlands on Mars.

Evaluation of slip ratio correlations in two-phase flow

Critical flow is one of the essential parameters in LOCA accident analysis in which pressure difference is very high. Void fraction (α), in another term, slip ratio, s, is the key parameter that could affect critical flow prediction. Henry-Fauske (HF) model is the model for critical flow calculation existing in current computer codes such as MARS, RELAP, TRACE. However, the limitation of this model is slip ratio s=1. By modified the slip ratio correlation, the paper focuses on evaluating the HF model. Among the chosen correlations for slip ratio, Smith correlation is the best option for this purpose. The results in our paper showed that while the original Smith correlation with k=0.4 is suggested for horizontal tests, the modified one with k=0.2 could be applied for vertical tests.