Search Results

This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

A dimensionless relationship that estimates the maximum bearing load of a 4-cylinder 4-stroke in-line engine has been found. This relationship may assist the design engineer in choosing a desired counterweight mass. It has been demonstrated that: 1) the average bearing load increases with engine speed and 2) the maximum bearing load initially decreases with engine speed, reaches a minimum, then increases quickly with engine speed. This minimum refers to a transition speed at which the contribution of the inertia force overcomes the contribution of the maximum pressure force to the maximum bearing load. The transition speed increases with an increase of counterweight mass and is a function of maximum cylinder pressure and the operating parameters of the engine.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

Inerters have become a hot topic in recent years, especially in vehicle, train, and building suspension systems. The performance of a passive inerter and a semi-active inerter was analyzed and compared with each other and it showed that the semi-active inerter has much better performance than the passive inerter, especially with the Hybrid control method. Eight different layouts of suspensions were analyzed with a quarter car model in this paper. The adaptation of dimensionless parameters was considered for a semi-active suspension and the semi-active inerters. The performance of the semi-active inerter suspensions with different layouts was compared with a semi-active suspension with a conventional parallel spring-damper arrangement. It shows a semi-active suspension, with more simple configuration and lower cost, has similar or better compromise between ride and handling than a semi-active inerter with the Hybrid control.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.

An autonomous vehicle is a comprehensive intelligent system that includes environment sensing, vehicle localization, path planning and decision-making control, of which environment sensing technology is a prerequisite for realizing autonomous driving. In the early days, vehicles sensed the surrounding environment through sensors such as cameras, radar, and lidar. With the development of 5G technology and the Vehicle-to-everything (V2X), other information from the roadside can also be received by vehicles. Such as traffic jam ahead, construction road occupation, school area, current traffic density, crowd density, etc. Such information can help the autonomous driving system understand the current driving environment more clearly. Vehicles are no longer limited to areas that can be sensed by sensors. Vehicles with different autonomous driving levels have different adaptability to the environment.

Taking a good longitudinal braking performance on flat and level road of tractor and semi-trailer combination as a target, in order to achieve an ideal braking force distribution among axles, while the vehicle deceleration is just depend on the driver's intention, not affected by the variation of semi-trailer mass, the paper proposes a model based vehicle mass identification and braking force distribution strategy. The strategy identifies the driver's braking intention via braking pedal, estimates semi-trailer's mass during the building process of braking pressure in brake chamber, distributes braking force among axles by using the estimated mass. And a double closed-loop regulation of the vehicle deceleration and utilization adhesion coefficient of each axle is presented, in order to eliminate the bad effect of mass estimation error, and enhance the robustness of the whole algorithm. A simulation is conducted by utilizing MATLAB/Simulink and TruckSim.

The Modular Automotive Technology Testbed (MATT) is a flexible platform built to test different technology components in a vehicle environment. This testbed is composed of physical component modules, such as the engine and the transmission, and emulated components, such as the energy storage system and the traction motor. The instrumentation on the tool enables the energy balance for individual components on drive cycles. Using MATT, a single set of hardware can operate as a conventional vehicle, a hybrid vehicle and a plug-in hybrid vehicle, enabling direct comparison of petroleum displacement for the different modes. The engine provides measured fuel economy and emissions. The losses of components which vary with temperature are also measured.

A new friction testing system has been designed and built to simulate the actual engine conditions in friction and wear test of piston-ring and cylinder liner assembly. Experimental data has been developed as Friction Coefficient / Crank Angle Degree diagrams including the effects of running speed (500 and 700 rpm) and ring normal load. Surface roughness profilocorder traces were obtained for tested samples. Mixed lubrication regime observed in the most part of the test range. New cylinder bore materials and lubricants can be screened easily and more reliable simulated engine friction data can be collected using this technique.

A new formulation is developed for the ignition delay (ID) in diesel engines to account for the effect of piston motion on the global autoignition reaction rates. A differentiation is made between the IDe measured in engines and IDv, measured in constant volume vessels. In addition, a method is presented to determine the coefficients of the IDe correlation from actual engine experimental data. The new formulation for IDe is applied to predict the misfiring cycles during the cold starting of diesel engines at different low ambient temperatures. The predictions are compared with experimental results obtained on a multi-cylinder heavy-duty diesel engine.

Transport vehicles consume a large amount of fuel with low efficiency, which is significantly affected by drivers' behaviors. An assessment system of eco-driving pattern for buses could identify the deficiencies of driver operation as well as assist transportation enterprises in driver management. This paper proposes an assessment method regarding drivers' economic efficiency, considering driving conditions. To this end, assessment indexes are extracted from driving economy theories and ranked according to their effect on fuel consumption, derived from a database of 135 buses using multiple regression. A layered structure of assessment indexes is developed with application of AHP, and the weight of each index is estimated. The driving pattern score could be calculated with these weights.

The earth's fossil energy is not limitless, and we should be taking advantage of the highly developed fields of science and technology to utilize it more efficiently and to create a fully environmentally friendly life. Considering the prodigious amount of vehicles in the world today, even a small improvement in their energy-saving performance could have a significant impact. In this paper, a new type of electro-hydraulic power steering (EHPS) system is described. It has two main advantages. First, it can significantly decrease the demand on the motor so that it can be used for a wider range of vehicles. Second, its pressure-flow characteristic can be programmed and is more flexible than hydraulic power steering (HPS) system. A prototype with a 500 W motor was applied to a truck with a front load of 2,700 kg, and static steer sweep tests were conducted to validate its feasibility.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

Mobility assessment for combat vehicles is often a great challenge for the military due to various subjective attributes. The attributes' characteristics vary significantly depending on the vehicle type and its operating environments such as terrain, weather, and human factors. A clear definition and relationship between multiple attributes including human factors is necessary to assess mobility. To the best of authors' knowledge, many existing mobility assessment techniques use complex analytical methods and focus on individual attributes. In this paper, for the first time, the authors propose a novel approach to define vehicle mobility and its influencing attributes using qualitative linguistic fuzzy variables, which are defined as having values between 0 and 1. The authors also propose a fuzzy logic mobility (FLM) model and a simulation approach to assess a combat vehicle's mobility.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.