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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.

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.

Velocity prediction on hilly road can be applied to the energy-saving predictive control of intelligent vehicles. However, the existing methods do not deeply analyze the difference and diversity of road slope driving characteristics, which affects prediction performance of some prediction method. To further improve the prediction performance on road slope, and different road slope driving features are fully exploited and integrated with the common prediction method. A rolling prediction-based multi-scale fusion prediction considering road slope transition driving characteristics is proposed in this study. Amounts of driving data in hilly sections were collected by the advanced technology and equipment. The Markov chain model was used to construct the velocity and acceleration joint state transition characteristics under each road slope transition pair, which expresses the obvious driving difference characteristics when the road slope changes.

This paper presents a study of LPG lean burn in a motorcycle SI engine. The lean burn limits are compared by several ways. The relations of lean burn limit with the parameters, such as engine speed, compression ratio and advanced spark ignition etc. are tested. The experimental results show that larger throttle opening, lower engine speed, earlier spark ignition timing, larger electrode gap and higher compression ratio will extend the lean burn limit of LPG. The emission of a LPG engine, especially on NOx emission, can be significantly reduced by means of the lean burn technology.

Internal combustion engines, as the dominant power source in the transportation sector and the primary contributor to carbon emissions, face both significant challenges and opportunities in the context of achieving carbon neutral goal. Biofuels, such as biodiesel produced from biomass, and zero-carbon fuel ammonia, can serve as alternative fuels for achieving cleaner combustion in internal combustion engines. The dual-fuel combustion of ammonia-biodiesel not only effectively reduces carbon emissions but also exhibits promising combustion performance, offering a favorable avenue for future applications. However, challenges arise in the form of unburned ammonia (NH3) and N2O emissions. This study, based on a ammonia-biodiesel duel-fuel engine modified from a heavy-duty diesel engine, delves into the impact of adjustments in the two-stage injection strategy on the combustion and emission characteristics.

To satisfy the power and energy requirement of the systems, such as electrical vehicles, the battery packs are constructed with hundreds of single cells connected in series and parallel connection. The most significant difference between a single cell and a battery pack is cell-to-cell variation. Not only does cell-to-cell variation have a big effect on the available energy and power of the battery packs, but also it causes early degradation of battery and potential safety issues. The cell variation effects on battery packs are widely studied because it is of great significance for battery sorting and management scheme. In this paper, battery pack inconsistency is clearly defined and the resulting battery capacity loss and aging acceleration problems are analyzed in detail. A comprehensive LiFePO4 battery pack model was established, which has taken into account cell-to-cell variation, thermal model, capacity degradation, resistance increasing and different battery topologies.

Advanced compression ignition combustion system which reduces simultaneously both nitride oxides (NOx) and particulate matter (PM) is a promising approach to meet future emission regulations. In order to achieve advanced compression ignition, flexible fuel injection is required for ultra-early and post-TDC injections, which conventional injector fails to accomplish due to wall-wetting effect. In this work, special injectors with the spray angle of 60 degree are applied on a 4 cylinder mass-production diesel engine without modification of the engine configuration. For application-oriented study, sweep experiments of injection timings and durations, fuel injection pressure and the boost pressure are carried out to investigate the relationships between the control parameters and the engine performance. Model based calibration and real application tests validate the maximum applicable operation range of maximum speed of 2200 RPM and IMEP of 8.0 bar.

Metal foil is a widely used material in the automobile industry, which not only is the honeycomb barrier material but is also used as current collectors in Li-ion batteries. Plenty of studies proved that the mechanical property of the metal foil is quite different from that of the metal sheet because of the size effect on microscopic scale, as the metal foil shows a larger fracture stress and a lower ductility than the metal sheet. Meanwhile, the fracture behavior and accurate constitutive model of the metal foil with the consideration of the strain rate effect are widely concerned in further studies of battery safety and the honeycomb. This article conducted experiments on 8011H18 aluminum foil, aiming to explore the quasi-static and dynamic tension testing method and the anisotropic mechanical behavior of the very thin foil. Two metal foil dog-bone specimens and three types of notched specimens were tested with a strain rate ranging from 2 × 10−4/s to 40/s and various stress states.

This paper presents an experimental study of the emission characteristics of a small Spark-Ignited, LPG engine. A single cylinder, four-stroke, water-cooled, 125cc SI engine for motorcycle is modified for using LPG fuel. The power output of LPG is above 95% power output of gasoline. The emission characteristics of LPG are compared with the gasoline. The test result shows that LPG for small SI engine will help to reduce the emission level of motorcycles. The HC and CO emission level can be reduced greatly, but NOx emissions are increased. The emission of motorcycle using LPG shows the potential to meet the more strict regulation.

An air-cooled, four-stroke, 125 cc electronic gasoline fuel injection SI engine for motorcycles is altered to burn ethanol fuel. The effects of nozzle orifice size, fuel injection duration, spark timing and the excess air/ fuel ratio on engine power output, fuel and energy consumptions and engine exhaust emission levels are studied on an engine test bed. The results show that the maximum engine power output is increased by 5.4% and the maximum torque output is increased by 1.9% with the ethanol fuel in comparison with the baseline. At full load and 7000 r/min, HC emission is decreased by 38% and CO emission is decreased 46% on average over the whole engine speed range. However, NOx levels are increased to meet the maximum power output. The experiments of the spark timing show that the levels of HC and NOx emission are decreased markedly by the delay of spark timing.

The automotive industry is aggressively pursuing fuel efficiency improvements through hybridization of production vehicles, and there are an increasing number of racing series adopting similar architectures to maintain relevance with current passenger car trends. Hybrid powertrains offer both performance and fuel economy benefits in a motorsport setting, but they greatly increase control complexity and add additional degrees of freedom to the design optimization process. The increased complexity creates opportunity for performance gains, but simulation based tools are necessary since hybrid powertrain design and control strategies are closely coupled and their optimal interactions are not straightforward to predict. One optimization-related advantage that motorsports applications have over production vehicles is that the power demand of circuit racing has strong repeatability due to the nature of the track and the professional skill-level of the driver.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

The lightweight technology takes an important role in electric vehicle(EV) energy conservation domain, as lighter vehicle means less energy consumed under same condition. In this paper, the typical energy requirement in an NEDC cycle is investigated, and the relationship between lightweight rate and energy consumption reduction effectiveness is given. The benefit of lightweight to EV come from the less battery cost because of less energy requirement. For EVs, with less battery cost, a certain lightweight rate can be obtained with less total cost. On the other hand, if lightweight rate is very high, the battery cost won't be able to cover the lightweight cost. Besides, the relationship between driving range and battery capacity is discussed in this paper. It is found that there is a limitation of EV driving range, which is determined by the battery energy density.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Many types of brake by wire systems have been developed in past years, such as EMB (Electro-mechanical Brake) [1, 2], DEHB (Distributed Electro-hydraulic Braking System) [3] and EWB (Electric Wedge Brake) [4]. When the vehicle need braking in long period such as waiting for traffic light or downhill braking in those brake systems, the current will sustain very long time with very high level. This current will result in high temperature in motor, and will damage the power supplier. When a new DEHB is developing, a holding function is added in this DEHB. The holding function is self-energized when holding the brake, and automatic released after the brake. Advantageously, after activation of the holding function, the current delivered to the motor for braking is substantially decreased, especially, will be zero when the brake torque is not need to adjust.

The collision accidents of electric vehicles are gradually increasing, and the response of battery cell under mechanical abuse conditions has attracted more and more attention. In the real collision, the mechanical load on battery generally has the following characteristics, including multiple loading directions, dynamic impact and blunt intrusion. Therefore, it is necessary to study the mechanical response and deformation of battery under complex loading, especially in-plane dynamic loading condition. According to the actual accident, we designed the constrained blunt compression test of the battery in different speeds and directions. For out-of-plane loading, the structural stiffness of battery increases obviously and the fracture is advanced compared with the corresponding quasi-static tests. For in-plane constrained loading, the force response can be approximately divided into two linear segments, in which the structural stiffness increases abruptly after the inflection point.

The new control algorithm for parallel hybrid electric vehicle is presented systematically, in which engine operation points are limited within higher efficient area by the control algorithm and the state of charge (SOC) is limited in a range in order to enhance the batteries' charging and discharging efficiency. In order to determine the ideal operating point of the vehicle's engine, the control strategy uses a lookup table to determine the torque output of the engine. The off-line simulation model of parallel HEV power train is developed which includes the control system and controlled objective (such as engine, electric motor, battery pack and so on). The results show that the control algorithm can effectively limite engine and battery operation points and much more fuel economy can be achieved than that of conventional one.

Since road electric vehicles typically require a significantly variable and random load power demand in response to traffic conditions, such as frequent sequences of acceleration and deceleration and uphill followed by downhill runs. In this context, the energy management system of electric vehicle must ensure an effective power distribution between battery and supercapacitor to satisfy load demand. In this paper, the power management control strategy of hybrid energy storage system is developed by introducing terrain information to optimize system efficiency and battery lifetime. In this presented research, we aim at developing a power management control strategy considering the influence of the terrain information on system efficiency and battery lifetime.

In order to obtain a good understanding of mechanical behaviors of lithium-ion battery modules in electric vehicles, comprehensive experimental and numerical investigations were performed in the study. Mechanical indentation tests with different indentation heads, different loading directions and different impact speeds were performed on battery modules with prismatic cells. To mitigate thermal runaway, only fully discharged battery modules were used. The force-displacement responses and open circuit voltage were recorded and compared. It was found that the battery modules experienced different failure modes when subjected to mechanical abuse. Besides internal short circuit of cells, external short circuit from bus bar and vapor leakage of electrolyte were also found to deteriorate the mechanical and electrical integrity of the tested modules. Mechanical anisotropy and dynamic effect were found on the battery module.