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The authors present the supervisory control of a parallel hybrid powertrain, focusing on several issues related to the real-time implementation of optimal control based techniques, such as the Equivalent Consumption Minimization Strategies (ECMS). Real-time implementation is introduced as an intermediate step of a complete chain of tools aimed at investigating the supervisory control problem. These tools comprise an offline optimizer based on Pontryagin Minimum Principle (PMP), a two-layer real-time control structure, and a modular engine-in-the-loop test bench. Control results are presented for a regulatory drive cycle with the aim of illustrating the benefits of optimal control in terms of fuel economy, the role of the optimization constraints dictated by drivability requirements, and the effectiveness of the feedback rule proposed for the adaptation of the equivalence factor (Lagrange multiplier).

The use of reciprocating internal combustion engines (ICE) dominates the sector of the on-road transportation, both for passengers and freight. CO2 reduction is the present technological driver, considering the major worldwide greenhouse reduction targets committed by most governments in the western world. In the near future (2020) these targets will require a significant reduction with respect to today’s goals, reinforcing the importance of reducing fuel consumption. In ICEs more than one third of the fuel energy used is rejected into the environment as thermal waste through exhaust gases. Therefore, a greater fuel economy could be achieved if this energy is recovered and converted into useful mechanical or electrical power on board. For long haul vehicles, which run for hundreds of thousands of miles per year at relatively steady conditions, this recovery appears especially worthy of attention.

Internal combustion engines are actually one of the most important source of pollutants and greenhouse gases emissions. In particular, on-the-road transportation sector has taken the environmental challenge of reducing greenhouse gases emissions and worldwide governments set up regulations in order to limit them and fuel consumption from vehicles. Among the several technologies under development, an ORC unit bottomed exhaust gas seems to be very promising, but it still has several complications when it is applied on board of a vehicle (weight, encumbrances, backpressure effect on the engine, safety, reliability). In this paper, a comprehensive mathematical model of an ORC unit bottomed a heavy duty engine, used for commercial vehicle, has been developed.

The paper presents a new control strategy to compensate the mutual influence of multiple injections in diesel and HCCI engines. The approach is based on a control-oriented model of the process, which represents the dependencies between injection timing, rail pressure, and masses injected. The model is conveniently inverted to yield the injection timing required to obtain a desired mass pattern. The model-based compensator developed is calibrated against measurements taken both on a dedicated injection bench and on a HCCI engine test bench. The compensator is then implemented in the control unit of the latter and validated against measurements of fuel consumption.

Fuel consumption is an essential factor that requires to be minimized in the design of a vehicle powertrain. Simple energy models can be of great help - by clarifying the role of powertrain dimensioning parameters and reducing the computation time of complex routines aiming at optimizing these parameters. In this paper, a Fully Analytical fuel Consumption Estimation (FACE) is developed based on a novel GRaphical-Analysis-Based fuel Energy Consumption Optimization (GRAB-ECO), both of which predict the fuel consumption of light- and heavy-duty series hybrid-electric powertrains that is minimized by an optimal control technique. When a drive cycle and dimensioning parameters (e.g. vehicle road load, as well as rated power, torque, volume of engine, motor/generators, and battery) are considered as inputs, FACE predicts the minimal fuel consumption in closed form, whereas GRAB-ECO minimizes fuel consumption via a graphical analysis of vehicle optimal operating modes.

Due to more and more complex powertrain architectures and the necessity to optimize them on the whole driving conditions, simulation tools are becoming indisputable for car manufacturers and suppliers. Indeed, simulation is at the basis of any algorithm aimed at finding the best compromise between fuel consumption, emissions, drivability, and performance during the conception phase. For hybrid vehicles, the energy management strategy is a key driver to ensure the best fuel consumption and thus has to be optimized carefully as well. In this regard, the coupling of an offline hybrid strategy optimizer (called HOT) based on Pontryagin’s minimum principle (PMP) and an online equivalent-consumption-minimization strategy (ECMS) generator is presented. Additionally, methods to estimate the efficiency maps and other overall characteristics of the main powertrain components (thermal engine, electric motor(s), and battery) from a few design parameters are shown.

In modern turbocharged internal combustion engines the cooling of the air after the compression stage is the standard technique to reduce temperature of the engine intake air aimed at improving cylinder filling (volumetric efficiency) and, therefore, overall global efficiency. At present, standard values for the intake air temperature are in the range 30-70°C, dependently on engine load, external air conditions and vehicle speed and the adoption of a dedicated cooling fluid operating at low temperatures (-10-0°C) is addressed as the most viable option to achieve an effective temperature reduction. This paper investigates a pilot engine set-up, featuring an evaporator on the intake line of a turbocharged diesel engine, tested on a high speed dynamometer bench: the evaporator was a part of an air refrigeration unit – the same used for cabin cooling - composed also by a compressor, a condenser and a thermostatic expansion valve.

The growing interest on environmental issues related to vehicles is pushing up the research on reciprocating internal combustion engines which seems to be endless and able to insure to combustion engines a long future. Euro standards imposed a significant reduction of pollutant emissions and were the stimulus to favor the conception of technologies which represented real breakthroughs; the recent directives on greenhouse gases emissions further reinforced the concept of reducing fuel consumption and, consequently, carbon dioxide emissions. So, new technological efforts have to be made on internal combustion engines in order to achieve this additional target: several technological options are already available or under studying, but only a few of these are suitable, in particular, in terms of costs attendance per unit of CO2 saved. Among these technologies, a revision of engine cooling system seems to have good potentiality.

In this paper, an integrated simulation-based methodology demonstrating feasibility and performance of several electric-hybrid concepts is developed. Several advanced tools are coupled to define the specifications of each component of the hybrid powertrain, to select the most promising hybrid architecture and finally to assess the proposed powertrain with regard to CO2 and pollutants emissions. Concurrent minimization of NOx and CO2 emissions enables to find the best compromise to fulfil Euro 6 standards while lowering fuel consumption. This stage consists in an iterative co-optimization of the power split strategies between the electric drive and the Diesel engine and of the engine settings (injection pressure, EGR rate, etc.). The methodology combines optimal control laws and optimization methodology based on global statistical models using single-cylinder design of experiments. After several iterations, this method allows to find the optimal NOx/CO2 trade-off curve.

The paper describes the derivation of a real-time controller for the energy management of a series hybrid city bus. The controller is based on Optimal Control theory and on a control-oriented model of the propulsion system. The model is of the quasi-stationary, backward type, and it is derived from tabulated data of the single components provided by the manufacturers and basic, first-principle equations. The fuel consumption obtained with the optimal controller is compared with that yielded by a conventional controller tracking the battery state-of-charge.

Hybrid propulsion systems can give an effective contribution to compensate the low on-board energy storage capability of pure electric vehicles. The prediction of the performance of a hybrid thermal-electric vehicle is complex, due to the interaction of several components exchanging different kind of energy among them. A detailed model is required for the components selection, sizing and optimization, as well as for a model based control. This paper describes the theoretical and experimental activities developed at DOE for setting up a Hybrid City Minibus. A preliminary model validation has been carried out with in field data, evidencing the possibility to obtain a fully model based vehicle control.

Literature showed quite clearly that the efficiency of Air to Fuel Ratio (AFR) control for Spark Ignition (SI) Internal Combustion Engines (ICE) strongly depends on its capacity to deal with the fuel-flow phenomena inside intake manifolds. Moreover, engine performances (such as power output, specific fuel consumption, and exhaust gas emissions) are directly related to the efficiency of the combustion process, which, on its turn, can be affected substantially by the air/fuel ratio variations related to the fuel-film dynamics. In this work a comprehensive model-based air/fuel ratio control technique is proposed: this is based on a dynamical model of the air dynamics inside inlet manifolds and on the online identification of the fuel-film parameters. Here the identification procedure is illustrated in detail and validated basing on experimental data regarding a single-cylinder engine.

Energy recovery in reciprocating internal combustion engines (ICE) is one of the most investigated options for the reduction of fuel consumption and GHG emissions saving in the transportation sector. In fact, the energy wasted in ICE is greater than that converted in mechanical form. The contribution associated with the exhaust gases is almost one third of the fuel energy, calling for an urgent need to be recovered into mechanical form. An extensive literature is oriented toward this opportunity, strongly oriented to ORC (Organic Rankine Cycle)-based power units. From a thermodynamic point of view, one option, not extensively explored, is certainly represented by the Inverted Brayton Cycle (IBC) concept and by the corresponding components which make possible this recovery.

In the perspective of fuel saving and emissions reduction, engine oil thermal management has not yet received the attention it deserves. Lubricating oil, in fact, should be the focus of a specific warmup action: the expected benefits is on friction reduction – mechanical efficiency improvement – but also on a positive interaction with the cooling fluid thermal dynamics. The lower thermal capacity of the circulating oil (with respect to the cooling fluid) and the instantaneous reduction of the viscosity due to temperature increase produces a faster engine overall efficiency benefit: this invites to focus specific actions on its thermal management in the direction of speeding up the temperature rise during a cold engine starting.

A smart way to reduce CO2 emission in transportation sector is to recover energy usually wasted and re-use it for engine and vehicle needs. ORC plant on exhaust gas of ICE is really interesting, but it has a significant impact on the exhaust line and vehicle's weight. The backpressure realized in the exhaust and the weight gain, in fact, produce a specific fuel consumption increase as well as an increase in the propulsion power: both terms could vanish the energy recovered. The paper discusses the effects of the pressure losses produced by an ORC plant mounted on the exhaust line of an IVECO F1C test bench engine. The interactions produced on the turbocharged engine have been experimentally investigated: the presence of an IGV turbocharger makes the effect of the backpressure not straightforward to be predicted and needed a full experimental testing of the group in order to understand its reaction and the net effect in terms of specific fuel consumption.

Waste Heat Recovery (WHR) is one of the most viable opportunities to reduce fuel consumption and CO2 emissions from internal combustion engines in the transportation sector. Hybrid thermal and electrical propulsion systems appear particularly interesting because of the presence of an electric battery that simplifies the management of the electrical energy produced by the recovery system. The different technologies proposed for WHR can be categorized into direct and indirect ones, if the working fluid operating inside the recovery system is the exhaust gas itself or a different one whose sequence of transformations follows a thermodynamic cycle. In this paper, a turbocharged diesel engine (F1C Iveco) equipped with a Variable Geometry Turbine (VGT) has been tested to assess the energy recoverable from the exhaust gases both for direct and indirect recovery.

Improving the development of electrified vehicles requires finding efficient methods for the component sizing of complex powertrains, since they may require a control optimization (for the energy management) which, when added to the sizing optimization, significantly increases the design space. A methodology to estimate the fuel consumption with a closed-form expression is found in the literature, which can be used to reduce the control/plant co-optimization to a static optimization problem. This approach can be used by either estimating the consumption of an existing powertrain: the descriptive level; or by predicting how the consumption will vary with the sizing parameters of the powertrain components: the predictive level. In previous works, the descriptive level was applied to the Toyota Mirai, a Fuel Cell Hybrid Electric Vehicle, showing that it can be extended to vehicles with a fuel cell system.

With the increase of heavy-duty transportation, more fuel efficient technologies and services have become of great importance due to their environmental and economical impacts for the fleet managers. In this paper, we first develop a new analytical model of the heavy-truck for its dynamics and its fuel consumption, and valid the model with experimental measurements. Then, we propose a bi-level optimization approach to reduce the fuel consumption, thus the CO2 emissions, while ensuring several safety constraints in real-time. Numerical results show that important reduction of the fuel consumption can be achieved, while satisfying imposed safety constraints.

Fuel consumption reduction and CO2 emissions saving are the present drivers of the technological innovation in Internal Combustion Engines for the transportation sector. Among the numerous technologies which ensure such benefits, the role of the cooling pump has been recognized, mainly referred to the possibility to improve engine performances during warm up. During engine homologation, an additional benefit on the fuel consumption can be also reached reducing the energy demand of the pump. In fact, during the cycle, propulsion power requested by the vehicle is low and the importance of the energy absorbed by the pump became significant, since the pump operates far from its maximum efficiency.

Accurately predicting the future behavior of the surrounding traffic, especially the velocity of the lead vehicle is important for optimizing the energy consumption and improve the safety of Connected and Automated Vehicles (CAVs). Several studies report methods to predict short-to-mid-length lead vehicle velocity using stochastic models or other data-driven techniques, which require availability of extensive data and/or Vehicle-to-Vehicle (V2V) communication. In the absence of connectivity, or in data-restricted cases, the prediction must rely only on the measured position and relative velocity of the lead vehicle at the current time. This paper proposes two velocity predictors to predict short-to-mid-length lead vehicle velocity. The first predictor is based on a Constant Acceleration (CA) with an augmented stop mode. The second one is based on a modified Enhanced Driver Model (EDM-LOS) with line-of-sight feature.