Implications of path tolerance and path characteristics on critical vehicle manoeuvres

Path planning and path following are core components in safe autonomous driving. Typically, a path planner provides a path with some tolerance on how tightly the path should be followed. Based on that, and other path characteristics, for example, sharpness of curves, a speed profile needs to be assigned so that the vehicle can stay within the given tolerance without going unnecessarily slow. Here, such trajectory planning is based on optimal control formulations where critical cases arise as on-the-limit solutions. The study focuses on heavy commercial vehicles, causing rollover to be of a major concern, due to the relatively high centre of gravity. Several results are obtained on required model complexity depending on path characteristics, for example, quantification of required path tolerance for a simple model to be sufficient, quantification of when yaw inertia needs to be considered in more detail, and how the curvature rate of change interplays with available friction. Overall, in situations where the vehicle is subject to a wide range of driving conditions, from good transport roads to more tricky avoidance manoeuvres, the requirements on the path following will vary. For this, the provided results form a basis for real-time path following.     

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.     

Gain scheduled linear quadratic tracking system tuned optimally by covariance matrix adaption evolutionary strategy for automotive engine coldstart control

In this paper, a gain scheduled linear quadratic tracking system (LQTS) tuned optimally by an evolutionary strategy (ES) is devised to reduce the total tailpipe hydrocarbon (HC) emissions of an automotive engine over the coldstart period. As the engine’s behavior during coldstart operations is nonlinear, the system dynamics is clearly analyzed and represented by a number of separate linear models generated based on a coldstart model verified by experimental data. An independent LQTS is then implemented for each of these linear models. In this way, several control laws are created, and the corresponding gains are calculated for each of the independent control laws. ES is then used to tune the adjustable parameters of LQTSs to calculate the control inputs, namely air/fuel ratio (AFR) and spark timing (Δ), such that the resulting exhaust gas temperature (T _exh) and engine-out HC emissions (HC _raw) be close to a set of optimum profiles. This enables the controller reduce the cumulative tailpipe hydrocarbon emissions (HC _cum) to the highest possible extent. To demonstrate the acceptable performance of the proposed controller, an optimal controller derived from the Pontryagin’s minimum principle (PMP) is also taken into account. Based on the results of the conducted comparative study, it is shown that the proposed control technique has a very good performance, and also, can be easily used for real-time applications, as it consumes a remarkably trivial computational time for calculating the controlling commands.     

Experimental and 3D,embedded modeling for diesel engine SCR deposit

Nowadays, the selective catalytic reduction (SCR) is a promising solution to fulfill stringent nitrogen oxide (NO_X) emission standards enforced by worldwide regulation bodies for lean burning engines. However, in the practical operation, urea deposits occur under unfavorable conditions, which bring about a failure of urea dosing strategy, affect the SCR system de-NOx performance and lowering the fuel economy by increasing the engine back pressure. This paper will present 3D deposit model, which can be used to predict the deposit position. Furthermore, a model-based controls strategy and calibration are designed. The comparison test results of both engine emission tests and vehicle field tests shows there is significant deposits improvement with the embedded model.     

Optimal design of three-planetary-gear power-split hybrid powertrains

Many of today’s power-split hybrid electric vehicles (HEVs) utilize planetary gears (PGs) to connect the powertrain elements together. Recent power-split HEVs tend to use two PGs and some of them have multiple modes to achieve better fuel economy and driving performance. Looking to the future, hybrid powertrain technologies must be enhanced to design hybrid light trucks. For light trucks, the need for multi-mode and more PGs is stronger, to achieve the required performance. To systematically explore all the possible designs of multi-mode HEVs with three PGs, an efficient searching and optimization methodology is proposed. All possible clutch topology and modes for one existing configuration that uses three PGs were exhaustively searched. The launching performance is first used to screen out designs that fail to satisfy the required launching performance. A near-optimal and computationally efficient energy management strategy was then employed to identify designs that achieve good fuel economy. The proposed design process successfully identify 8 designs that achieve better launching performance and better fuel economy, while using fewer number of clutches than the benchmark and a patented design.     

Novel stability control strategy for distributed drive electric vehicle based on driver operation intention

In this paper, a novel direct yaw control method based on driver operation intention for stability control of a distributed drive electric vehicle is proposed. It was discovered that the vehicle loses its stability easily under an emergency steering alignment (EA) problem. An emergent control algorithm is proposed to improve vehicle stability under such a condition. A driver operation intention recognition module is developed to identify the driving conditions. When the vehicle enters into an EA condition, the module can quickly identify it and transfer the control method from normal direct yaw control to emergency control. Two control algorithms are designed. The emergency control algorithm is applied to an EA condition while the adaptive control algorithm is applied to other conditions except the EA condition. Both simulation results and real vehicle results show that: The driver module can accurately identify driving conditions based on driver operation intention. When the vehicle enters into EA condition, the emergent control algorithm can intervene quickly, and it has proven to outperform normal direct yaw control for better stabilization of vehicles.     

Finite element damage analysis of an underwater glider–ship collision

Underwater gliders, which are profiling autonomous underwater vehicles designed to make oceanographic measurements, are increasingly used in the coastal ocean. As they regularly surface for data transmission, gliders increasingly pose a risk for fast ships. In order to estimate the extent of damage due to collision, 3D finite element simulations of collisions between a glider and a high-speed craft with a glass-fiber reinforced plastic hull are performed. Different collision scenarios such as impact locations, angles of attack and speeds are examined. The results are compared to an analytical solution based on simplifying assumptions. Although both methods reveal consistent results, it is shown that finite element simulations are required to account for the 3D shape of the ship. The results indicate that at ship velocities exceeding 7.5 m/s (14.6 kt) the glider penetrates the ship’s hull causing severe damage to its structure.     

特殊分段的精度控制方法探讨

在明确了分段精度控制意义及概念的前提下,对分段精度控制计划和精度控制管理过程作了详细分析,并制定相应的控制方法。首先针对舵臂分段,根据其尾部曲率较大以及不规则性,依据挂舵垂直性控制其精度;然后针对尾轴分段,根据同心度和尾轴管的定位控制该分段的精度;再针对主基座分段,主要根据基座面板水平度来控制该分段的精度;最后总结出典型分段精度控制方法。     

C型独立液货舱开孔处结构强度分析与研究

C型独立液货舱开孔区域的强度对整个液货舱围护系统的安全性至关重要。根据压力容器规范计算方法对罐体上气室处开孔及气室封头上的接管处开孔进行强度校核,并提出补强设计方案;通过有限元计算方法对补强方案进行验证与研究。结果表明,气室处开孔应力水平较高,通过设置复板及增加气室筒体板厚的方式能最有效改善该区域的强度。     

Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation

A transit service quality study based on cluster analysis was performed to extract detailed customer profiles sharing similar appraisals concerning the service. This approach made it possible to detect specific requirements and needs regarding the quality of service and to personalize the marketing strategy. Data from various customer satisfaction surveys conducted by the Transport Consortium of Granada (Spain) were analyzed to distinguish these groups; a decision tree methodology was used to identify the most important service quality attributes influencing passengers’ overall evaluations. Cluster analysis identified four groups of passengers. Comparisons using decision trees among the overall sample of all users and the different groups of passengers identified by cluster analysis led to the discovery of differences in the key attributes encompassed by perceived quality.