The power supply, fuel consumption, and noxious emissions of a vehicle depend on the use that is made of it. Usually [1] only the driving cycle is considered to be a sufficient way to gauge a vehicle's usage. It is not, however, enough. Experimental tests have proved that, while similar driving cycles entail similar power demand, fuel consumption and emissions differ. In addition, a driving cycle, usually a synthesis [1-7] of several cycles collected experimentally, represents neither a specific link of the road network nor a specific user. Vehicle use must, accordingly, be described by something more comprehensive than the driving cycle, and this might be called the ‘use cycle’, for which a definition needed to be found. For a definition of the use cycle, all possible factors influencing vehicle emissions had to be examined. It was thus necessary to develop a tool both for gathering data that might reveal a different use of the vehicle and for identifying factors that might have an influence on emissions. The easiest, cheapest, and most versatile way to collect real data on the use of a vehicle is to use the vehicle's own sensors connected to the on-board diagnostic (OBD-2) port. Readings from a GPS can provide some characteristics related to the vehicle's position. This paper describes the development of a tool for collecting real-time OBD and GPS information. The acquisition tool was validated by a number of tests on a dynamometer chassis and differences are never higher than 3 per cent (e.g. on speed max 2 km/h). The first result obtained on vehicle usage is that driver behaviour influences throttle position independently of the driving cycle. Even with similar driving cycles, the accelerator pedal position and its variations turned out to be heavily different, suggesting a new definition of driver behaviour linked to the way the driver uses the pedals. Such pedal movement does have an influence on the air-fuel ratio, which remains stable around the stoichiometric value with ‘calm’ use of the accelerator, while it changes continuously, never becoming stoichiometric, with ‘aggressive’ accelerator behaviour. The continuous use of the developed tool on large fleets of vehicles will allow progress along this path and help define use cycles that may then be used by car manufacturers to design vehicles more efficient in their different uses and by the authorities to force more stringent homologation rules.

As electric mobility becomes more important every day, scientific research brings us new solutions that increase performance, reduce financial and economic impacts and increase the market share of electric vehicles. Therefore, there is a necessity to compare technical and economic aspects of different technologies for each transport application. This article presents a comparison of three bus prototypes in terms of dynamic performance. The analysis is based on the collection of real data (acceleration, maximum speed and energy consumption) under different settings. Each developed prototype uses the same bus chassis but relies on different energy storage systems. Results show that the dynamic bus performance is independent on the three energy storage technologies, whereas technologies affect the management costs, charging time and available range. An extensive experimental analysis reveals that the bus equipped with a hybrid storage (lithium-ion batteries and supercapacitors) had the most favorable net present value, in comparison with storage composed of only lead–acid or lithium-ion batteries. This result is due to the greater life of lithium-ion batteries and to the capability of supercapacitors, which reduce both batteries depth of discharge and discharge rate.

In the research results presented here, an average driving cycle is synthesized for an electrically driven car moving in the city of Rome. The technique of Lyons et al. [1] for synthesizing a statistically representative driving cycle was used on a 5 week acquisition set of data collected with a duly equipped electric Citroen Saxo that was driven for over 3100 km by six different drivers in the months of May and June 2001 in Rome. The driving cycle developed is compared with the other available cycles, especially the European ones. The comparison highlights the need for this new dedicated cycle to represent the driving conditions of electric cars in Rome, with a lower value of the acceleration-speed product on account of the limited power of the electric vehicle, frequent changes in the acceleration sign, typical of the trafic in a big city, and a very high maximum speed, typical of the driving behaviour of the inhabitants of Rome.

Introduction: Hybrid technology is seen by many as a potential solution to reduce vehicle emissions in cities. However type approval tests of hybrid vehicles measure emission levels comparable to those of conventional cars in the same market segment. It has been argued that type approval tests do not represent the reality of emission in cities therefore, to quantify the real emission of hybrids and to compare them with those of conventional vehicles in the same conditions, an emission measurement campaign was organised. Acquisition campaign: Three Honda cars, one conventional (the Civic 2.0) and two hybrids (the Civic IMA and the Civic Hybrid), equipped to collect emissions as well as the engine and vehicle working parameters were driven three times by twenty drivers on the same urban route. Drivers were asked to drive normally and not requested to do anything special but to scrupulously follow the given itinerary. Results: Two main results were obtained: average and maximum emission levels for the three cars are quantified; the effects of the drivers on such levels assessed. The conventional car (with two people and 250 kg of measurement tools onboard) consumes an average of 12.6 l/100 km, its CO2 emissions range between 200 g/km and 300 g/km with an average of 260 g/km. CO emissions range between 0.25 g/km and 6.25 g/km (Euro IV limit is 1 g/km) with an average of 2 g/km. The most recent of the two tested hybrids consume in average 8.23 l/100 km and emits between 150 and 230 g/km of CO2 with an average of about 180 g/km; it emits virtually no CO in the majority of cases but can reach up to 1.8 g/km and average CO emissions are about 0.2 g/km. The hybrid performs always better than the conventional; in terms of CO2 and consumption it can have up to a 30% reduction and in terms of CO up to 90% reduction. Conclusions: The wideness of the measured ranges depends mostly on the drivers. Women tend to consume and emit less than men. The reason for this is the different way they use the accelerator pedal; they push it less and keep it steadier. In other word the standard deviation of the accelerator position (or throttle) is lower. It is here shown how a correlation exist between the throttle standard deviation and the emissions which justify using such parameter as the indicator of drive-style.

Transport planning and mobility management is nowadays of paramount importance, particularly in the urban context where innovative, sustainable, smart, and green mobility solutions are required to satisfy the citizen’s needs. Such ambitious objective requires a multidisciplinary research approach to address the problem from different perspectives from urban and geographical analysis to social studies including 3D mapping and urban infrastructure analysis. To collect and manage huge amount of data acquired and produced, big data and IOT/IOE technologies are exploited together with 3D city digital twin representations of the urban scenario to simulate, plan and evaluate urban policies and guide the urban development of the future. In this paper, the activities that will be carried out by an interdisciplinary group of researchers of the University of Florence, within the sustainable mobility centre (MOST), are presented and discussed.