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In the past two decades, rapidly expanding economy in China led to burst in travel demand and pursuit of quality of life. It further promoted the rapid growth of China's passenger car market. China had already become the largest vehicle sales country, exceeding the U.S. in 2010. By the end of 2018, there had been over 240 million cars in China, with over 200 million passenger cars. The surge of car ownership has also brought a series of problems, like traffic congestion, long commuting time, insufficient parking space, etc. Therefore, some local governments in China introduced vehicle purchase restriction policies to control the growth and gross of vehicle stock. Different cities issued different rules. Lottery and auction mechanisms both exist. There are also differences in classification and licensing of electric vehicles. However, with the recent slowdown of economic development, China's car sales began to decline in 2018, and the trend of 2019 is also not optimistic.

A personal computer-based vehicle powertrain simulation (VPS) is developed to predict fuel economy and performance. This paper summarizes the governing equations used in the model. Then the different simulation techniques are described with emphasis on the more complicated time-dependent simulation. The simulation is validated against constant speed and variable cycle test track data obtained for a 5 ton army truck. Then the simulation is used to compare the performance of the 5 ton truck when powered by a cooled and natually aspirated engine, a cooled and turbocharged engine, and an uncooled and turbocharged engine. Studies of the effect of payload, tire efficiency, and drag coefficient on vehicle performance are also conducted, as well as a performance comparison between manual and automatic transmissions. It is concluded that the VPS code can provide good predictions of vehicle fuel economy, and thus is a useful tool in designing and evaluating vehicle powertrains.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

Compared with conventional vehicles, electric vehicles (EVs) offer the benefits of replacing petroleum consumption and reducing air pollutions. However, there have been controversies over greenhouse gas (GHG) emissions of EVs from the life-cycle perspective in China’s coal-dominated power generation context. Besides, it is in doubt whether the cost-effectiveness of EVs in China exceeds other fuel-efficient vehicles considering the high prices. In this study, we compared the life-cycle GHG emissions of existing vehicle models in the market. Afterwards, a cost model is established to compare the total costs of vehicles. Finally, the cost-effectiveness of different vehicle types are compared. It is concluded that the GHG emission intensity of EVs is lower than reference and hybrid vehicles currently and is expected to decrease with the improvement of the power grid.

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.

This study investigates the impact of transient engine operation on the emissions formed during a tip-in procedure. A medium-duty production V-8 diesel engine is used to conduct experiments in which the rate of pedal position change is varied. Highly-dynamic emissions instrumentation is implemented to provide real-time measurement of NOx and particulate. Engine subsystems are analyzed to understand their role in emissions formation. As the rate of pedal position change increases, the emissions of NOx and particulates are affected dramatically. An instantaneous load increase was found to produce peak NOx values 1.8 times higher and peak particulate concentrations an order of magnitude above levels corresponding to a five-second ramp-up. The results provide insight into relationship between driver aggressiveness and diesel emissions applicable to development of drive-by-wire systems. In addition, they provide direct guidance for devising low-emission strategies for hybrid vehicles.

An early-design methodology for predicting both expected fuel economy and catalyst-out CO, HC and NOx concentrations during arbitrarily-defined transient cycles is presented. The methodology is based on utilizing a vehicle-powertrain model with embedded maps of fully warmed up engine-out performance and emissions, and appropriate temperature-dependent correction factors to account for not fully warmed up conditions during transients. Similarly, engine-out emissions are converted to catalyst-out emissions using conversion efficiencies based on the catalyst brick temperature. A crucial element of the methodology is hence the ability to predict heat flows and component temperatures in the engine and the exhaust system during transients, consistent with the data available during concept definition and early design phases.

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.

Modern diesel engines manufactured for commercial vehicles are calibrated to meet EPA emissions regulations. Many of the technologies and strategies typically incorporated to meet emissions targets compromise engine performance and efficiency. When used in military applications, however, engine performance and efficiency are of utmost importance in combat conditions or in remote locations where fuel supplies are scarce. This motivates the study of the potential to utilize the flexibility of emissions-reduction technologies toward optimizing engine performance while still keeping the emissions within tolerable limits. The study was conducted on a modern medium-duty International V-8 diesel engine with variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR). The performance-emissions tradeoffs were explored using design of experiments and response surface methodology.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

Hybrid electric vehicle (HEV) is regarded as an important technology in solving the energy and environment crisis. In this paper, the HEV technology applied in passenger cars by major automotive OEMs such as Toyota, Honda, GM, Ford, Volkswagen, BMW are investigated. The configuration diagrams for each OEM are presented. Based on the architecture analysis, a classification is done according to similar structures and performances. Furthermore, a cost estimation methodology for HEV is presented based on the preliminary tear-down research done by Environment Protection Agency (EPA). Meanwhile, the logarithmic relationship between fuel consumption (FC) reduction and degree of hybridization (DOH) is discovered by investigating 30 different hybrid cars. Combining the cost estimation and relation between FC&DOH, the hybridization cost for cars to meet the FC regulations can be calculated.

Fuel cell vehicle and battery electric vehicle are two environmentally benign vehicle technology types possibly meeting the zero-emission regulations in the future. The premise is they can achieve parity with conventional vehicle both environmentally and economically. Besides, it is necessary to distinguish which technology is more suitable in China's current and future context. This paper compares their cost-effectiveness for reducing greenhouse gas emissions, examining the life-cycle greenhouse gas emissions of conventional gasoline vehicle, battery electric vehicle and fuel cell vehicle in China's energy context under three different scenarios. The results indicate that under the 500km drive range, fuel cell vehicles are less competitive than battery electric vehicles currently. Fuel cell vehicles generate much more greenhouse gas emissions than battery vehicles and conventional gasoline vehicles.

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.

The new technological revolution is promoting the intelligent upgrade of vehicles. Traditional vehicles are gradually developing into intelligent connected vehicles (ICVs). New features such as autonomous driving, smart cockpits, and Internet of Vehicle of ICVs have brought users safe, comfortable and interesting travel experiences. Vehicle software, containing a wealth of functions and continuously outputting valuable data, has become the core of the definition of vehicle functions. Traditional vehicle hardware has gradually decoupled from software and become standardized, modular and shared resources. At present, the era of Software-Defined Vehicle (SDV) is coming soon, which is bound to bring subversive changes to both vehicle technologies and industrial ecologies. However, the lack of comprehensive understanding and the clear development way of SDV are ubiquitous in all kinds of corporations in vehicle industry. This will make them be caught off guard when SDV really comes.

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.