Analysis of the Operating Costs of Passenger Cars Declared by Vehicles' Manufacturers and Obtained by Users

Every year, there are more and more cars on the roads that cause pollution. To reduce it, conventional vehicles have started to be replaced by electric and hybrid vehicles. Therefore, the average fuel/energy consumption of electric, hybrid, spark ignition and self-ignition vehicles over a test distance of 100 km was investigated. The test results were then compared to the manufacturer's data and the average difference between the manufacturer's data and the test data is shown. The largest average difference in fuel consumption between the manufacturer's data and the test data was observed for hybrid vehicles (over 230 %) and the smallest for electric vehicles (less than 10 %) and spark ignition vehicles (almost 18 %). Considering costs, the largest difference between manufacturer's data and test data is observed, as in the previous case, in electric vehicles (0.25 €) and the largest in hybrid vehicles (almost 6 € per 100 kilometers driven).

Optimal Control for Cleaner Hybrid Vehicles: A Backward Approach

This work presents an application of the optimal control theory to find trade offs between fuel consumption and pollutant emissions (CO, HC, NOx) of sustaining hybrid vehicles. Both cold start and normal operations are considered. The problem formulation includes two state variables: battery state of energy and catalyst temperature; and three control variables: torque repartition between engine and motor, spark advance, and equivalence ratio. Optimal results were obtained by delaying the first engine crank after the urban part of the mission. The results show that a quick catalyst light off is performed. Once the catalyst is primed, special control parameters values are adopted to operate the engine.

Economic, Ecological and Social Analysis Based on DEA and MCDA for the Management of the Madrid Urban Public Transportation System

The aim of this research is to help public transport managers to make decisions on the type of buses that should compose their public transport fleet, taking into account economic, environmental and social criteria from the point of view of sustainability. This paper fills a knowledge gap by including the social dimension of sustainability in addition to the economic and environmental dimensions. The original nature of this study lies in analyzing complementarities in the structuring of an efficiency and multicriteria problem. Our research analyzes Madrid public bus system data; the problem is structured in a comparative way between two analytical methods, a Data Envelopment Analysis (DEA) and an ELimination Et Choice Translating REality (ELECTRE) III. Our research results show that two main groups of vehicles could play a part in part the theoretical solution. The main conclusions of this research are that (a) plug-in and induction electric vehicles are not comparable to GNC and diesel–hybrid vehicles in terms of cost, pollution and service; and (b) the ELECTRE III model provides more information in solving this problem than the DEA model.

Layout analysis of compressed air and hydraulic energy storage systems for vehicles

The compressed air energy storage system has a better energy density, while the widely used hydraulic one is superior in power performance. Therefore, they are suitable for different hybrid vehicles, which require a comparative study on the performances and vehicle applicability of the broad pressure energy storage system layouts. In this paper, an integrated mathematical model of four basic pressure layouts is presented for characteristic analysis and applicability discussion. Results show that the open volume layout achieves the best power performance with the flow specific power of 13.92 MJ/m3, thus it is suitable for heavy hybrid trucks and mobile machinery. The open mass layout achieves the best energy performance with the energy density of 124.35 MJ/m3, which can be used in light new energy passenger vehicles. And the performance of the closed volume layout is close to the open volume layout with the flow specific power of 9.78 MJ/m3, so it could be applied to middle and light hybrid trucks. This research provides a basis for the hybrid method of pressure energy storage system layouts for vehicles, and could be applied in the design and research of non-electric hybrid vehicles in the near future.

The Development of CO2 Instantaneous Emission Model of Full Hybrid Vehicle with the Use of Machine Learning Techniques

Road transport contributes to almost a quarter of carbon dioxide emissions in the EU. To analyze the exhaust emissions generated by vehicle flows, it is necessary to use specialized emission models, because it is infeasible to equip all vehicles on the road in the tested road sections with the Portable Emission Measurement System (PEMS). However, the currently used emission models may be inadequate to the investigated vehicle structure or may not be accurate due to the used macroscale. This state of affairs is especially related to full hybrid vehicles, since there are none of the microscale emission models that give estimated emissions values exclusively for this kind of drive system. Several automakers over the past decade have invested in hybrid vehicles with great opportunities to reduce costs through better design, learning, and economies of scale. In this work, the authors propose a methodology for creating a CO2 emission model, which takes relatively little computational time, and the models created give viable results for full hybrid vehicles. The creation of an emission model is based on the review of the accuracy results of methods, such as linear, robust regression, fine, medium, coarse tree, linear, cubic support vector machine (SVM), bagged trees, Gaussian process regression (GPR), and neural network (NNET). Particularly in the work, the best fit for the road input data for the CO2 emission model creation was the GPR method. PEMS data was used, as well as model training data and model validation. The model resulting from this methodology can be used for the analysis of emissions from simulation tests, or they can be used for input parameters for speed, acceleration, and road gradient.

Evaluation of the Effect of Chassis Dynamometer Load Setting on CO2 Emissions and Energy Demand of a Full Hybrid Vehicle

Among the solutions that make it possible to reduce CO2 emissions in the transport sector, particularly in urban traffic conditions, are hybrid vehicles. The share of driving performed in electric mode for hybrid vehicles is highly dependent on motion resistance. There are different methods for determining the motion resistance function during chassis dynamometer testing, leading to different test results. Therefore, the main objective of this study was to determine the effect of the chassis dynamometer load function on the energy demand and CO2 emissions of a full-hybrid passenger car. Emissions tests according to the New European Driving Cycle (NEDC) were carried out on a chassis dynamometer for three different methods of determining the car’s resistance to motion. The study showed that adopting the motion resistance function according to different methods, results in differences in CO2 emissions up to about 35% for the entire cycle. Therefore, the authors suggest that in the case of tests carried out with chassis dynamometers, it is necessary to also provide information on the chassis dynamometer loading function adopted for the tests.

Dispatching Design for Customized Bus of Hybrid Vehicles Based on Reservation Data

Proper vehicle operation and route planning are critical for achieving the best match between bus operation and passenger services. In order to enhance the attractiveness of public transportation, a new type of the public transportation dispatching method based on passenger reservation data is proposed. This mode can meet the requirements of multiple lines in urban centers during peak hours, which can realize direct service between two stations. Then, taking the lowest operating cost of the enterprise and the lowest passenger waiting cost as the optimization goal, a customized dynamic dispatching model of multiline and hybrid vehicles was established. Finally, a calculation example is designed and the genetic algorithm is used to solve the model. The results show that the hybrid vehicle solution is more reasonable than the traditional single-vehicle solution and reveal that the model is feasible to optimize scheduling plan. The conclusions obtained in this research lay a theoretical foundation for APP setup and operation plan formulation.