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The field of automotive engineering has devoted much research to reduce fuel consumption to attain sustainable energy usage. Friction reductions in powertrain components can improve engine fuel economy. Quantitative accounting of friction is complex because it is affected by many physical aspects such as oil viscosity, temperature, surface roughness and component rotation speed. The purpose of this paper is two-fold: first, to develop a useful tool for evaluating the friction in engine and accessories based on test data; second, to exercise the tool to evaluate the fuel economy gain in a drive cycle for several friction reduction technologies.

Conventional viscous shock absorbers, in parallel with suspension springs, passively dissipate the excitation energy from road irregularity into heat waste, to reduce the transferred vibration which causes the discomfort of passengers. Energy-harvesting shock absorbers, which have the potential of conversion of kinetic energy into electric power, have been proposed as semi-active suspension to achieve better balance between the energy consumption and suspension performance. Because of the high energy density of the rotary shock absorber, a rotational energy-harvesting shock absorber with mechanical motion rectifier (MMR) is used in this paper. This paper presents the assessment of vehicle dynamic performance with the proposed energy-harvesting shock absorber in braking process. Moreover, a PI controller is proposed to attenuate the negative effect due to the pitch motion.

In low-temperature environment, heat supply requires considerable energy, which significantly increases energy consumption and shortens the mileage of electric vehicle. In the fuel cell vehicles, waste heat generated by the fuel cell system can supply heat for vehicle. In this paper, a thermal management system is designed for a the fuel cell interurban bus. Thermal management strategy aiming at temperature regulation for the fuel cell stack and the passenger compartment and minimal energy consumption is proposed. System model is developed and simulated based on AMESim and Matlab/Simulink co-simulation. Simulation results show that the fuel cell system can provide about 78 % energy of maximum heat requirement in -20 °C ambient temperature environment.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

The transportation sector in the United States is a major contributor to global energy consumption and carbon dioxide emission. To assess the future potentials of different technologies in addressing these two issues, we used a family of simulation programs to predict fuel consumption for passenger cars in 2020. The selected technology combinations that have good market potential and could be in mass production include: advanced gasoline and diesel internal combustion engine vehicles with automatically-shifting clutched transmissions, gasoline, diesel, and compressed natural gas hybrid electric vehicles with continuously variable transmissions, direct hydrogen, gasoline and methanol reformer fuel cell hybrid electric vehicles with direct ratio drive, and battery electric vehicle with direct ratio drive.

The traditional vacuum booster is gradually replaced by Brake-by-Wire system (BBW) in modern passenger car, especially Electric Vehicle (EV). Some mechanical and hydraulic components are replaced by electronic components in Brake-by-Wire system. Using BBW system in modern passenger vehicles can not only improve the automotive safety performance, reliability and stability, but also promote vehicle maneuverability, comfort, fuel economy and environmental protection. Although vehicle's braking performance is greatly improved by using BBW, the system will inevitably consume some energy of the vehicle power supply, thus introducing unexpected drawback in comparison with the traditional vacuum assist braking system, since it doesn't need any electric power. Therefore, the analysis of energy consumption on typical main cylinder booster based BBW system under typical driving cycles will contribute to advanced design of current advanced braking system.

Electric vehicles maintain the fastest development in China and undertake the responsibility of optimizing energy consumption and carbon emission in the transportation field. However, from the entire life cycle point of view, although electric vehicles have a certain degree of energy consumption and carbon emission reduction in the use phase, they cause extra energy consumption and carbon emission in the manufacturing phase, which weakens the due environmental benefits to some extent. The recycling of electric vehicles can effectively address the issue and indirectly reduce the energy consumption and carbon emission in the manufacturing phase. China is setting up the recycling system and strengthening regulation force to achieve proper energy consumption and carbon emission reduction benefits of electric vehicles. Under the current electric vehicle recycling technologies, China can reduce about 34% of carbon emission in electric vehicle manufacturing phase.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

The driving power system can be combined with lasers, lights, etc., and applied to automobiles to achieve various functions. Under the general trend of the development of intelligent vehicles, people have higher and higher requirements for the accuracy and power of various equipment. However, as power increases, how to ensure the stability of factors such as current is a challenging problem. Therefore, it is extremely important to study and design a high-power drive system in this paper, so as to ensure a stable output of the current. The system is composed of power supply, load, secondary power supply and control chip. The choice of power supply and load is conventional model. The secondary power supply adopts step-down circuit, with synchronous rectifier chip, which can effectively reduce energy consumption, and with temperature protection device, which can ensure the safe and reliable operation of equipment.

Many kinds of drive systems can be adopted by a pure electric vehicle. In order to select the most suitable drive system, the configuration features of different drive systems were analyzed. After matching the drive systems in a pure electric vehicle, the dynamic performance comparison has been carried out; and on the basis of establishing the vehicle energy consumption model and taking the city driving cycle as an example, the economic comparison of these drive systems has been completed.

This paper presents a new magnetorheological braking which can be used in vehicles. Magneto-rheological (MR) fluid is a novel material which can be used in different components of vehicle. Magneto-rheological fluids (MRF) are suspensions of micron size whose yield stress varies rapidly as the change of magnetic field. The use of MRF in vehicles has been gaining popular recently due to its strong rheological effect, fast response and low energy consumption. Besides, these performances give designers more choice in automotive designs. However, most of the related research of MRF brake is about the construction of small prototype to verify its rheological performance. As a result, research progress is limited to calculation and simulation which make the braking force of prototype can hardly meet the requirement of vehicle due to a lack of optimal design and the understanding of MRF in the situation of high sheer stress and magnetic field.

As the only energy storage component in the internal combustion engine vehicles (ICEVs), the battery is lack of comprehensive supervision and effective protection. Excessive discharge or aging cannot be detected and dealt with, which may lead to damage of the battery, even startup failure of the vehicle. In this paper, a full protection and optimization management scheme of the battery is proposed, to achieve comprehensive protection of the battery and energy optimization. Firstly, power partitioning model of the battery is established to reveal the battery characteristics in different states, which divides the battery into several function zones. Then, based on the power partitioning model, over discharge protection and graded overcurrent protection method are proposed, to achieve full protection of the battery. Thirdly, energy optimization management strategy based on generator’s multimode operation is introduced.

Both the economy and energy demand increase rapidly in China. The government is facing severe problems from energy security, carbon emissions and environmental issues. The past trends and future plans of energy will have great influence on the transportation, construction and industry development. This paper summarizes the present and future energy structure in China. Conventional fossil energy, nuclear energy and renewable energy are all included. Electricity will account for more proportion in total energy consumption in the future, and the structure of electricity will be cleaner. That will promote the development of electric vehicles and the transformation of China’s automotive industry. The optimization of energy structure will accelerate the low-carbon development in China. China’s energy development will enter a new stage from the expansion of total quantity to the upgrading of quality and efficiency.

In recent years, Magneto-rheological (MR) fluid has drawn a lot of attention for its applications in a variety of torque transmission devices, such as brakes, clutches and soft starters of mechanical equipment. Compared with the conventional clutch of vehicle, the novel MR clutch has the advantages of fast response with electronic signal, accuracy control and simple structure without mechanical wear in plates. Besides, MR clutch may be helpful to fast response of vehicle in some situation. Nowadays, most applications of MR fluids in the torque transmission field mainly are used in low-power situation. As far as we know, the proposed effective methods enhancing the output torque of MR devices will increase either the number of fluid gaps or the magnetic field in the MR fluid. This article presents a novel vehicle clutch utilizing magnetorheological fluid and multiple-disc structure.

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.

An analysis method for characterizing fuel behavior during spark-ignition engine starting has been developed and applied to several sets of start-up data. The data sets were acquired from modern production vehicles during room temperature engine start-up. Two different engines, two control schemes, and two engine temperatures (cold and hot) were investigated. A cycle-by-cycle mass balance for the fuel was used to compare the amount of fuel injected with the amount burned or exhausted as unburned hydrocarbons. The difference was measured as “fuel unaccounted for”. The calculation for the amount of fuel burned used an energy release analysis of the cylinder pressure data. The results include an overview of starting behavior and a fuel accounting for each data set Overall, starting occurred quickly with combustion quality, manifold pressure, and engine speed beginning to stabilize by the seventh cycle, on average.

As vehicles become electrified and more intelligent in terms of sensing, actuation and processing; a number of interesting possibilities arise in controlling vehicle dynamics and driving behavior. Over-actuation with in- wheel motors, all wheel steering and active camber is one such possibility, which facilitate the control strategies that push boundaries in energy consumption and safety. Optimal control can be used to investigate the best combinations of control inputs to an over-actuated system. This paper shows how an optimal control problem can be formulated and solved for an over-actuated vehicle case, and highlights the translation of this optimal solution to a real-world scenario, enabling intelligent means to improve vehicle efficiency. This paper gives an insight into Dynamic Programming (DP) as an offline optimal control method that guarantees the global optimum.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.