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Hybrid electric vehicles (HEVs) are worldwide recognized as one of the best and most immediate opportunities to solve the problems of fuel consumption, pollutant emissions and fossil fuels depletion, thanks to the high reliability of engines and the high efficiencies of motors. Moreover, as transport policy is becoming day by day stricter all over the world, moving people or goods efficiently and cheaply is the goal that all the main automobile manufacturers are trying to reach. In this context, the municipalities are performing their own action plans for public transport and the efforts in realizing high efficiency hybrid electric buses, could be supported by the local policies. For these reasons, the authors intend to propose an efficient control strategy for a hybrid electric bus, with a series architecture for the power-train.

Lithium ion batteries are the most promising candidates for electric and hybrid electric vehicles, owe to their ability to store higher electrical energy. As a matter of fact, in automotive applications, these batteries undergo frequent and fast charge and discharge processes, which are associated to internal heat generation, which in turns causes temperature increase. Thermal management is therefore crucial to keep temperature in an appropriate level for safe operation and battery wear prevention. In a recent work authors have already demonstrated the capabilities of a coupled lattice Boltzmann-Finite Volume Method to deal with thermal transient of a three-dimensional air-cooled Li-ion battery at different discharging rates and Reynolds numbers. Here, in order to improve discharge thermal capabilities and reduce temperature levels of the battery itself, a layer of porous medium is placed in contact with the battery so to replace a continuum solid aluminum layer.

Highway and roadway surface measurement is a practice that has been ongoing for decades now. This sort of measurement is intended to ensure a safe level of road perturbances. The measurement may be conducted by a slow moving apparatus directly measuring the elevation of the road, at varying distance intervals, to obtain a road profile, with varying degrees of resolution. An alternate means is to measure the surface roughness at highway speeds using accelerometers coupled with high speed distance measurements, such as laser sensors. Vehicles out rigged with such a system are termed inertial profilers. This type of inertial measurement provides a sort of filtered roadway profile. Much research has been conducted on the analysis of highway roughness, and the associated metrics involved. In many instances, it is desirable to maintain an off-road course such that the course will provide sufficient challenges to a vehicle during durability testing.

To accurately evaluate the energy consumption benefits provided by connected and automated vehicles (CAV), it is necessary to establish a reasonable baseline virtual driver, against which the improvements are quantified before field testing. Virtual driver models have been developed that mimic the real-world driver, predicting a longitudinal vehicle speed profile based on the route information and the presence of a lead vehicle. The Intelligent Driver Model (IDM) is a well-known virtual driver model which is also used in the microscopic traffic simulator, SUMO. The Enhanced Driver Model (EDM) has emerged as a notable improvement of the IDM. The EDM has been shown to accurately forecast the driver response of a passenger vehicle to urban and highway driving conditions, including the special case of approaching a signalized intersection with varying signal phases and timing. However, most of the efforts in the literature to calibrate driver models have focused on passenger vehicles.

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.

This paper presents a sensitivity analysis-based study aimed at robustly calibrating the parameters of an adaptive energy management strategy designed for a Plugin Hybrid Electric Vehicle (PHEV). The supervisory control is developed from the Pontryagin's Minimum Principle (PMP) approach and applied to a model of a GM Chevrolet Volt vehicle. The proposed controller aims at minimizing the fuel consumption of the vehicle over a given driving mission, by achieving a blended discharge strategy over the entire cycle. The calibration study is conducted over a wide set of driving conditions and it generates a look-up table and two constant values for the three controller parameters to be used in the in-vehicle implementation. Finally, the calibrated adaptive control strategy is validated against real driving cycles showing the effectiveness of the calibration approach.

To encourage electric mobility, governments may pay part of the price of the new car. An economic evaluation of this incentive program is proposed. The economic value results from a comparison between the with-incentive scenario and the without-incentive counterfactual scenario. Four contributions are considered: the change in consumers’ welfare, the government expenditure, the change in the discounted costs of energy consumption for the portion that is purchased abroad, and the change in the discounted costs of well-to-wheel greenhouse gas emissions. A logit model is used to represent choices between differentiated cars and the consumption of all other goods in the economy (the numéraire). The car market in Italy in 2019 had incentives for all-electric and plug-in hybrid electric cars. In a worst case where no consumer scraps the old car the economic value is negative. The economic value is positive in the best case where all scrap.

This paper shall present the design and development of a family of high power, high-speed transport and combat vehicles based on a common module. The system looks to maximize performance at both high-speed operation and low-speed, heavy/severe-duty operation. All-wheel drive/steer-by-wire autonomous traction modules provide the basis for the vehicle family. Each module can continuously develop 300-400 kW of power at the wheels and has nearly double peak capability, exploiting the flexibility of the electric traction system. The maximum starting tractive effort developed by one module can reach 10-15 tons, and the full rated power can be produced at speeds of 100 mph. This paper will present the design and layout of the autonomous modules. Details will be provided about the tandem electric axles, with electric differentials and independent steering.

Battery electric vehicles (BEVs) are considered one of the most promising solution to improve the sustainability of the transportation sector aiming at a progressive reduction of the dependence on fossil fuels and the associated local pollutants and CO2 emissions. Presently, the major technological obstacle to a large scale diffusion of BEVs, is the fairly low range, typically less than 300 km, as compared to classical gasoline and diesel engines. This limit becomes even more critical if the electric vehicle is operated in severe weather conditions, due to the additional energy consumption required by the cabin heating, ventilating, and air-conditioning (HVAC). The adoption of vapor-compression cycle, either in heat pump or refrigerator configuration, represents the state-of-the-art technology for HVAC systems in vehicles. Such devices typically employ an expansion valve to abruptly reduce the pressure causing the flash evaporation of the working fluid.

The port-logistic industry has a significant impact on the urban environment nearby ports and on the surrounding coastal areas. This is due to the use of large auxiliary power systems on ships operating during port stays, as well as to the employment of a number of fossil fuel powered road vehicles required for port operations. The environmental impact related to the use of these vehicles is twofold: on one hand, they contribute directly to port emissions by fuel consumption; on the other hand, they require some of the ship auxiliary systems to operate intensively, such as the ventilation system, which must operate to remove the pollutants produced by the vehicle engines inside the ship. The pathway to achieve decarbonization and mitigation of energy use in ports involves therefore the adoption of alternative and cleaner technology solutions for the propulsion systems of such port vehicles.

Delivery trucks and vans represent a growing transportation segment which reflects the shift of consumers towards on-line shopping and on-demand delivery. Therefore, electrification of this class of vehicles is going to play a major role in the decarbonization of the transportation sector and in the transition to a sustainable mobility system. Hybrid electric vehicles can represent a medium-term solution and have gained an increasing share of the market in recent years. These vehicles include two power sources, typically an internal combustion engine and a battery, which gives more degrees of freedom when controlling the powertrain to satisfy the power request at the wheels. Components sizing and powertrain energy management are strongly coupled and can make a substantial impact on the final energy consumption of a hybrid vehicle.

Plug-In Hybrid Vehicles (PHEVs) represent the middle point between Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs), thus combining benefits of the two architectures. PHEVs can achieve very high fuel economy while preserving full functionality of hybrids - long driving range, easy refueling, lower emissions etc. These advantages come at an expense of added complexity in terms of available fuel. The PHEV battery is recharged both though regenerative braking and directly by the grid thus adding extra dimension to the control problem. Along with the minimization of the fuel consumption, the amount of electricity taken from the power grid should be also considered, therefore the electricity generation mix and price become additional parameters that should be included in the cost function.

Building and testing of physical prototypes for optimization purposes consume significant amount of time, manpower and financial resources. Mathematical formulation and solution of vehicle multibody dynamics equations are also not feasible because of the massive size of the problem. This paper proposes a methodology for vehicle design optimization that does not involve physical prototyping or exhaustive mathematics. The proposed method is fast, cost effective and saves considerable manpower. The methodology uses an industry acknowledged multibody dynamics simulation software (ADAMS) and a flexible architecture to explore large design spaces.

Strong dependency on crude oil in most areas of modern transportation needs lead into a significant consumption of petroleum resources over many decades. In order to maximize the effective use of remaining resources, various types of powertrain topologies, such as hybrid configurations among fuel cell, electric battery as well as conventional IC engine, have been proposed and tested out for number of vehicle classes including a personal commuting vehicle. In this paper the vehicle parameters are based on a typical commercial sub-compact vehicle (FIAT Panda) and energy needs are estimated on the sized powertrain. The main control approach is divided in two categories: off-line global optimization with dynamic programming (DP, not implementable in real time), and on-line Proportional and Feed-Forward with PI controllers. The proposed control approaches are developed both for charge-sustaining and charge-depleting mode and sample results are shown and compared.

The aim of this paper is to document a three year process of product development of the Formula Lightningtm electric race car constructed at the Ohio State University. Today interest in electric vehicles (EV's) is growing, due to the technological advances in recent years, but also in part due to recent legislation which mandates the introduction of ‘zero emission vehicles’ in California before the end of the century. The definition of ‘zero emission vehicle’ is: a vehicle which does not emit any pollutants during operation. Technologically, the only near term vehicle which meets this definition is an EV. One of the most difficult problems of electric racing is that the usable energy in a given set of batteries is not as easily determined as the amount of fuel in a tank. Also, the motor controllers may limit power output as battery voltage drops, further decreasing the amount of usable energy in a battery set.

A methodology has been developed to generate military vehicle driving cycles for use in vehicle simulation models. This methodology is based upon the mission profile for a vehicle, which is typically given within a vehicle's specifications and lists the types of terrains that the vehicle is likely to encounter. A simplistic vehicle powertrain and road load model and the Bekker vehicle-soil interaction model are used to estimate the vehicle performance over each type of terrain. Two types of driving cycles are generated within a Graphical User Interface developed within MATLAB using the results of the vehicle models: Linear modes driving cycles, and Real-world driving cycles.

This paper introduces a new series of empirical mathematical models developed to characterize brake torque generation of pneumatically actuated Class-8 vehicle brakes. The brake torque models, presented as functions of brake chamber pressure and application speed, accurately simulate steer axle, drive axle, and trailer tandem brakes, as well as air disc brakes (ADB). The contemporary data that support this research were collected using an industry standard inertia-type brake dynamometer, routinely used for verification of FMVSS 121 commercial vehicle brake standards.

The port-logistic sector has a crucial role in goods transport, as the 85-90% of international trade is achieved by means of maritime routes. The latest reports from the International Maritime Organization show that the port-logistic related activities are an important source of air pollution, both for the use of large auxiliary power systems on ships, which operate during port stays, as well as for the employment of fossil fueled road vehicles for on-site operations. As a matter of fact, the most important maritime facilities are located nearby urban areas and therefore reduction of the environmental impact in ports becomes of primary importance. Thus, in the pursuit of a greener in-port mobility, a progressive replacement of fossil fuels with cleaner alternatives must be promoted. This paper presents the analysis of the performance of a hydrogenfueled plug-in fuel cell/battery hybrid vehicle for cargo-handling in roll-on and roll-off port operations.

The objective draw by this project is to develop tools for Plug-in Hybrid Electric Vehicle (PHEV) design, energy analysis and energy management, with the aim of analyzing the effect of design, driving cycles, charging frequency and energy management on performance, fuel economy, range and battery life. A Chevrolet Equinox fueled by bio diesel B20 has been hybridized at the Center for Automotive Research (CAR), at The Ohio State University. The vehicle model has been developed in Matlab/Simulink environment, and validated based on laboratory and test. The PHEV battery pack has been modeled starting from Li-Ion batteries experimental data and then implemented into the simulator. In order to simulate “real world” scenarios, custom driving cycles/typical days were identified starting from average driving statistics and well-known cycles.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.