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课程概述 Powertrain controls for NEVs are one of the most complex and highly confidential areas of NEV research and development.  This two-day course takes the seemingly complicated field of NEV powertrain controls and summarizes it into a few basic principles.  The latest and most popular NEV powertrains are also reviewed to illustrate these principles and the controls strategies used.  对于新能源汽车来说，动力总成控制一直以来都是最复杂的和高度机密的领域之一。在这两天的课程中，我们将把看似复杂的动力总成控制系统总结出几条基本规则，同时，通过对当今其他车型动力控制系统的案例分析，来把这些规则和原理进行融会贯通。

This 4-week virtual-only experience is conducted by leading experts in the autonomous vehicle industry and academia. You’ll develop an understanding of the fundamentals of AV architecture, including mechatronics, kinematics, and the sense-think-act framework in autonomous systems. The course builds a connection for how robotics are used in autonomous vehicles and provides you with demonstrations, procedures, and the skills necessary to program a robot with basic commands using the Robot Operating System (ROS).

The presentation describes technology developments and the integration of these technologies into new emission control systems. As in other years, the reader will find a wide range of topics from various parts of the world. This is reflective of the worldwide scope and effort to reduce diesel exhaust emissions. Topics include the integration of various diesel particulate matter (PM) and Nitrogen Oxide (NOx) technologies as well as sensors and other emissions related developments. Presenter Atsuo Kondo, NGK Insulators, Ltd.

Simulation-based tolerance analysis is the accepted standard for dimensional engineering in aerospace today. Sophisticated 3D model-based tolerance analysis processes enable engineers to measure variation in complex, often large, assembled products quickly and accurately. Best-in-class manufacturers have adopted Quality Intelligence Management tools for collecting and consolidating this measurement data. Their goal is to completely understand dimensional fit characteristics and quality status before commencing the build process. This results in shorter launch cycles, improved process capabilities, reduced scrap and less production downtime. This paper describes how to use simulation-based approaches to correlate the theoretical tolerance analysis results produced during engineering simulations to actual as-built results. This allows engineers to validate or adjust as-designed simulation parameters to more closely align to production process capabilities.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

Four-way, integrated, diesel emission control systems that combine selective catalytic reduction for NOx control with a continuously regenerating trap to remove diesel particulate matter were evaluated under real-world, on-road conditions. Tests were conducted using a semi-tractor with an emissions year 2000, 6-cylinder, 12 L, Volvo engine rated at 287 kW at 1800 rpm and 1964 N-m. The emission control system was certified for retrofit application on-highway trucks, model years 1994 through 2002, with 4-stroke, 186-373 kW (250-500 hp) heavy-duty diesel engines without exhaust gas recirculation. The evaluations were unique because the mobile laboratory platform enabled evaluation under real-world exhaust plume dilution conditions as opposed to laboratory dilution conditions. Real-time plume measurements for NOx, particle number concentration and size distribution were made and emission control performance was evaluated on-road.

Abstract The non-pneumatic tire (NPT) has been widely used due to its advantages of no run-flat, no need for air maintenance, low rolling resistance, and improvement of passenger comfort due to its better shock absorption. It has a variety of applications in military vehicles, earthmovers, the lunar rover, stair-climbing vehicles, etc. Recently, the Unique Puncture-Proof Tire System (UPTIS) NPT has been introduced for passenger vehicles. In this study, three different design configurations, viz., Tweel, Honeycomb, and newly developed UPTIS, have been compared. The effect of polyurethane (PU) material nonlinearity has also been introduced by applying five different nonlinear PU material properties in the spokes. The combined analysis of the PU material nonlinearity and spoke design configuration on the overall tire stiffness and spoke damage prediction is done using three-dimensional (3D) finite element modelling (FEM) simulations performed in ANSYS 16.0.

Abstract In this article performance of the innovative Crank-Lever Electromagnetic Damper (CLEMD) for an off-road vehicle suspension system is analyzed. To determine the characteristic behavior of the CLEMD, the damping force it provides on the suspension system is varied by changing the values of the damping coefficient in the simulations. Various parameters considered in the analyses include power regenerated, voltage, current, comfort, road-holding, etc. The behavior of all the parameters of the CLEMD is observed for an off-road vehicle by carrying out simulations on country roads since the off-road vehicles are subjected to higher road irregularities and hence provide an opportunity to regenerate a higher amount of power. A two-dimensional (2-D) model of a vehicle developed in SimMechanics is interfaced with a Simulink model of CLEMDs for the analyses.

Abstract This article applies a new method for the evaluation and estimation of real-life energy consumption of two different thermal management systems based on driving behavior in the course of the day. Recent attempts to find energy-efficient thermal management systems for electric and plug-in hybrid electric vehicles have led to using secondary loop systems as an alternative approach for meeting dynamic heating and cooling demands and reducing refrigerant charge. However, the additional layer of thermal resistance, which influences the system’s transient behavior as well as passenger compartment comfort during cool-down or heat-up, makes it difficult to estimate the annual energy consumption. In this article, the overall energy consumption of a conventional and a secondary loop system is compared using a new method for describing actual customers’ driving behavior in the course of the day.

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.

Abstract In this article, compared with traditional Remote Parameter Control (RPC), the iterative process is improved based on linear transfer function (TF) estimation of the nonlinear dynamic system. In the improved RPC, the iteration coefficient is designed according to the convergence condition of the nonlinear iterative process, so that the convergence level, convergence speed, and iteration stability could be improved. The difference between the traditional and the improved RPC iterative process is discussed, the RPC iterative process of the nonlinear system is analyzed, and channel decoupling for Multi-Input Multi-Output (MIMO) system based on eigen-decomposition of the system TF and linear TF estimation is introduced. It assumes that the eigenvector matrix of the system TF remains the same, and the linear TF in the iterative process is estimated and updated, which is used for iterative calculation.

Abstract Path tracking is an essential stage for vehicle safety control. It is more newsworthy than ever in the automotive context and especially for autonomous vehicle. The study proposes an optimal control method for path tracking problem in inverse vehicle handling dynamics. The proposed method generates an expected trajectory which guarantees minimum clearance to the prescribed path by identifying the optimal steering torque input. Based on this purpose, the path tracking problem, which is treated as an optimal control problem, is then solved by local collocation method and mesh refinement. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. The results show that using control variables as a mesh refinement function can capture the dramatic changes in state variables, and the efficiency improvement is more significant as the number of the grid points increases.

Abstract The dynamic characteristics of tires are critical in the overall vibrations of vehicles because the tire-road interface is the only medium of energy transfer between the vehicle and the road surface. Obtaining the natural frequencies and mode shapes of the tire helps in improving the comfort of the passengers. The vibrational characteristics of structures are usually obtained by performing conventional impact hammer modal testing, in which the structure is excited with an impact hammer and the response of the structure under excitation is captured using accelerometers. However, this approach only provides the response of the structure at a few discrete locations, and it is challenging to use this procedure for rotating structures. Digital Image Correlation (DIC) helps in overcoming these challenges by providing the full-field response of the structure.

Abstract It is reasonable to use a two-phase heat transfer loop (TPL) in a thermal control system (TCS) of spacecraft with large heat dissipation. One of the key elements of TPL is a heat-controlled accumulator (HCA). The HCA represents a volume which is filled with vapor and liquid of a single working fluid without bellows. The pressure in a HCA is controlled by the heater. The heat and mass transfer processes in the HCA can proceed with a significant nonequilibrium. This has implications on the regulation of TPL. This article presents a mathematical model of nonequilibrium heat and mass transfer processes in an HCA for microgravity conditions. The model uses the equations of mass and energy conservation separately for the vapor and liquid phases. Interfacial heat and mass transfer is also taken into account. It proposes to use the convective component k for the level of nonequilibrium evaluation.

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract Vehicle cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQIparticles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQIparticles is less than 1 while CAQICO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).

Abstract Catalytic converters, a primary component in most automotive emissions control systems, do not function well until they are heated substantially above ambient temperature. As the primary energy for catalyst heating comes from engine exhaust gases, plug-in hybrid electric vehicles (PHEVs) that have the potential for short and infrequent use of their onboard engine may have limited energy available for catalytic converter heating. This article presents a comparison of multiple hybrid supervisory control strategies to determine the ability to avoid engine cold starts during a blended charge-depleting propulsion mode. Full vehicle and catalytic converter simulations are performed in parallel with engine dynamometer testing in order to examine catalyst temperature variations during the course of the US06 City drive cycle. Emissions and energy consumption (E&EC) calculations are also performed to determine the effective number of engine starts during the drive cycle.

Abstract The ability of senior citizens as well as other members of the general population to engage in an effective manner with technology is of increasing importance as new and innovative technologies become available. While recognizing the challenges that technologies can have on different populations, the ability to interact successfully with new technologies will, for seniors, have important consequences that can affect their quality of life and those of their families in numerous and important ways. This study, building upon previous research, examines the major dimensions of decision-making regarding attitudes toward autonomous vehicle technologies (ATVs) and their use. The study utilized data from a study of senior citizens in the Dallas-Fort Worth (DFW) area and compared the results with a sample of graduate students from a local university.