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The energy and pollutants management of Hybrid Electric Vehicles (HEV) consists in determining at each instant the optimal torque split between the Internal Combustion Engine (ICE) and the Electric Motor (EM). This torque choice aims to minimize both fuel consumption and pollutants emissions. A critical piece of information in this context is the value of the Three-Way Catalyst Converter (3WCC) conversion efficiency. This value is highly dependent on the 3WCC temperature; it is hence of major importance to have an accurate estimation of it. Although the literature is abundant about simple 0D thermal models of 3WCC, it is tempting to implement a more accurate and consequently complex model. In particular, both moisture from the exhaust gases during engine start and from ambient air during cooling phases lead to the formation of a liquid water film on the monolith’s exchange surface, causing a strong temperature plateau during the warm-up phase. The water evaporation causing a delay in the 3WCC temperature increase, it could lead to a serious degradation of the pollutants emissions if not taken into account. This paper proposes hence a 1D thermal model including water phase changing that allows a 72% decrease in the 3WCC temperature estimation error during the warm up phase. This accuracy gain, occurring in a phase where the converter temperature has not reached its full efficiency, provides a 1-2% reduction in CO, HC and NOx emissions.

The State Of Charge (SOC) estimation of a Li-ion battery is still an open problem. The most classical method, Coulomb Counting (CC) is vulnerable to current measurement bias. Measuring the Open-Circuit Voltage (OCV) allows to correct the error accumulated by the CC method, but only after the battery has been unsolicited long enough. Regarding these deficiencies, advanced SOC estimation methods try to combine current and voltage information, and are either based on an Extended Kalman Filter (EKF), which represents a certain algorithmic complexity and is hard to calibrate, or on black-box methods. In particular, methods using a Neural Network (NN) have been investigated in the literature, but take usually into account only instantaneous information, failing to represent the dynamic of ion diffusion in the electrodes. By considering also a close-past current integral as an input, this paper proposes a NN model able to correct initial SOC estimation errors and handle current measurement bias, and achieving a better estimation performance than a classical NN model taking only instantaneous information as an input.

An important control problem in the automotive powertrain domain is related to the relative use of the two engines of Hybrid Electric Vehicles (HEVs). Aiming to minimize energy and pollutants emissions, this online optimal control problem is highly constrained by the automotive context: very low computing resources, hardly predictable future vehicle dynamic, and need for strong algorithmic robustness. In this framework, the paper proposes two enhancements to the literature reference method. First, an analytical resolution of the optimal control problem is explained, allowing both algorithmic efficiency and simplicity. In the context of Plug-In HEVs, this method needs a battery State of Charge discharge reference, as these vehicles aim to empty their battery in a trip between two charging stations. The literature method aiming to plan this reference at the beginning of the trip fails to conserve optimality in certain heterogeneous trips cases developed in the paper. The second improvement proposed in the paper is then a new method using light cartographic information to deal with problematic cases. This method allows to attain online the optimality of an offline Dynamic Programming algorithm benefiting from a total a priori knowledge of the future powertrain operating points.

In a century where the green energy is a vital challenge, research about wind turbine is taking its place to give an alternative solution to polluting and fossil energies. Various scales of studies are possible for wind turbine production and lifetime optimization, such as the farm, the wind turbine or the blade. In this study we focused on the alleviation of aerodynamic load fluctuations produced by airflow speed and incidence angle variations by means of active flow control. Wind turbine greatly loses its efficiency when faced to wind gusts, moreover, the blade life span is reduced by the load oscillations created by wind disturbances. Thus, a control technic based on a surface plasma actuator is studied to reduce lift oscillation and actively keep a constant lift. Plasma actuator is used to manipulate the air circulation around the blade, thus, the lift. Proofs of concepts are conducted thanks to experiments in a wind tunnel and through numerical modelling.

This paper aims to propose a real-time suitable method to tackle the problem of energy and pollutant management of Hybrid Electric Vehicles. Methods proposed in the literature often limit the underlying optimal control problem to single-instant optimizations (Paganelli, 2002) due to the difficulty of taking future into account and to onboard limited computational resources. The point of the present paper is to propose an online oriented method based on a long-term vehicle speed prediction, using cartographic information such as speed limitation, road curvature, traffic and road signs. Pontryagin Maximum Principle applied on this speed prediction signal allows to convert the optimal control problem into a root-finding problem. This problem is solved using a Pegasus algorithm initialized by a black-box method trained offline, allowing high computational efficiency. The results are near-optimal and significantly better than classical methods: in the real-driving trip used in this paper, forecasting-ECMS showed a consumption 1.1% better and NOx emissions 4.4% better than a SOC-feedback adaptive-ECMS.

European standards on pollutants have resulted in the systematic integration of a three-way catalytic converter (3WCC) on gasoline engines. The conversion efficiency of the 3WCC is strongly dependent on the temperature of the 3WCC itself. Knowing this temperature is a key element in predicting and minimizing the real quantities of pollutants that the gasoline engine rejects. Due to cost issues, it is really difficult to obtain this information through a direct measurement. This article presents a complete methodology for estimating exhaust gas and catalyst temperature in real time. The first step of this methodology consists of building a 1-dimensional physical model (1D model) of the 3WCC’s temperature. All of the parameters of this model are identified using some experimental data and a particle swarm optimization algorithm. The second step of the proposed methodology consists of using an extended Kalman filter algorithm to estimate all temperatures in real time from a linearized model based on the previous 1D physical model and a measurement downstream of the 3WCC. Every step of this methodology is validated using experimental data.

Testbed are used to tune and assess automotive engines. As more High Dynamic (HD) scenarios need to be simulated, the testbeds require Multi Input Multi Output (MIMO) and robust control systems. A cooperation involving a major testbed manufacturer and two university laboratories was therefore set up. This paper presents the Control-System Design (CSD) methodology developed from system identification to the design and assessment of the MIMO robust controller for a HD testbed coupled with a spark-ignition engine. It is specially highlighted how the entire process has been automated and simplified and how the fractional order based MIMO CRONE CSD has been parameterized to obtain the best performance. Experimental results show that the proposed fractional order based MIMO control system is able to improve robustness and decoupling.

This article aims to propose a real-time compatible strategy for the energy management of a compression-ignition Hybrid Electric Vehicle (HEV), under pollutants emissions constraints. First, an offline method is applied in order to obtain a performance reference. Then, an online-oriented approach based on Model Predictive Control (MPC) is described, and a projected gradient algorithm used to solve the successive optimal control problems is explicitly presented. Both approaches are compared through simulation and the results are validated through experimentation.

Car builders are facing restrictions on both fuel consumption (FC) and pollutant emissions. In this context, Diesel Hybrid Electric Vehicles (HEV) are an interesting solution since they are more fuel-efficient than their gasoline-powered counterparts. However, Diesel pollutants remain a concern as, despite the fact that particulate emissions are treated by the Diesel Particulate Filter (DPF), tailpipe NOx emissions are still problematic. Previous works have shown that a better FC to pollutants trade-off can be achieved if the Energy and Emissions Management Strategy (EEMS) of the HEV includes the pollutants downstream an After-Treatment System (ATS). For Diesel HEV, a previous approach which took into account the Selective Catalytic Reduction (SCR) has been applied. This paper aims to find a better trade-off by adding the Diesel Oxidation Catalyst’s (DOC) influence on the SCR’s efficiency. Consequently, three EEMS taking into account more or fewer ATS are calculated with the Dynamic Programming (DP) algorithm on the Worldwide Light vehicle Test Cycle (WLTC). Hence, each strategy is applied to the full energy and emission model in order to deduce a fuel consumption to tailpipe NOx tradeoff. The tradeoffs for each strategy are compared. As a result, all the strategies can reduce NOx emissions by 30% with a FC penalty of 3%. In addition, the three EEMS have shown similar FC/tailpipe NOx trade-offs but the EEMS that took ATS into account were able to produce 3% more engine-out NOx than the strategy with no ATS. To ensure the optimality of the solutions, the impact of the states’ discretization in the DP algorithm is investigated. Despite a high discretization level for each state, the SCR’s temperature variation is still over-approximated and might underestimate the benefit of a strategy considering the complete Diesel ATS.

International audience

As a result of the increased complexity of today's powertrains, the traditional ways of designing engine control systems essentially through ad hoc methods and experimental tuning will no longer provide the desired level of performance. In this paper, the design of a multi-SISO robust controller is described which accommodates many of today's demands on controller development of the automotive industry. The control problem treated here is the air path control of a turbocharged diesel engine with Exhaust Gas Recirculation (EGR). Simulation results show the good control performance of the proposed control which is finally compared to an Internal Model Control.

This paper proposes an extension of CRONE control and design for unstable, multiple time-delay multivariable plants with right half-plane (RHP) zeros. The CRONE control approach developed for multivariable square plants is based on third generation scalar CRONE methodology. The aim is to find a decoupling and stabilizing controller for the open-loop transfer matrix. Fractional order transfer functions are used to define all the components of the diagonal open-loop transfer matrix, β 0 i . Optimization gives the best fractional open-loop transfer matrix, β . Finally, frequency-domain system identification is used to find a robust controller K = G −1 β . When the plant is inversed, time-delays and RHP poles or zeros can appear on the denominator of the transfer matrix, G −1 . To achieve a stable controller some time-delays, RHP zeros and unstable poles must be included within the diagonal transfer function of the open-loop transfer matrix. To assess the proposed design, the CRONE control approach is applied to a distillation example.

International audience; This article proposes a strategy which works on the fuel consumption / pollutant compromise with a gasoline Hybrid Electric Vehicle (HEV). First, a pollutant-constrained optimal energy management is derived from the Pontryagin’s Minimum Principle (PMP). Using only one parameter and considering standardized pollutant emissions, this approach is validated on a high-fidelity HEV model. Then, an online approach called the Equivalent Consumption and Pollutant Minimization Strategy (ECPMS), is explained and applied on a Hybrid Hardware In the Loop (Hy-HIL) test bench. This strategy reproduces the fuel consumption / pollutant trade-off with one tuning parameter and reduces pollutant emissions for a light fuel consumption penalty.

International audience; This paper presents a frequency-domain methodology for robust systemcontrol design, and its application in airpath control of a real turbocharged Diesel engine with intake throttle and exhaust gas re-circulation system. The objective is to find a robust control-system which reduces pollutant emission. The three inputs (throttle, wastegate and EGR valves) and two outputs (airflow and boost pressure) of the airpath make the system complex. AMulti InputMulti Output (MIMO) fractional order approach called CRONE (French abbreviation which means robust control of a non integer order) is used to design a non-square control-system for this non-linear plant. Firstly, a multisine signal is used for the system-identification, the airpath inputs are excited around all operating points in order to find a linear model of the plant. Then, the frequency responses of a defined nominal plant and experimental plant are taken into account to design the MIMO control-system using the CRONE shaping approach which permits to maintain performance and robust stability around a wide set of operating points. Finally, pollutant emission results from a driving cycle in test-bench show the relevance of the proposed approach.

International audience; The paper proposes a generic methodology to incorporate constraints (pollutant emission, battery health, drivability) into on-line energy management strategies (EMSs) for hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs). The integration of each constraint into the EMS, made with the Pontryagin maximum principle, shows a tradeoff between the fuel consumption and the constraint introduced. As state dynamics come into play (catalyst temperature, battery cell temperature, etc.), the optimization problem becomes more complex. Simulation results are presented to highlight the contribution of this generic strategy, including constraints compared to the standard approach. These results show that it is possible to find an energy management strategy that takes into account an increasing number of constraints (drivability, pollution, aging, environment, etc.). However, taking these constraints into account increases fuel consumption (the existence of a trade-off curve). This trade-off can be sometimes difficult to find, and the tools developed in this paper should help to find an acceptable solution quickly.

Although the CRONE Control System Design toolbox for Matlab makes it possible to optimize the parameters of robust controllers, it appears that the performance of the optimized controllers depends on the users' experience. New optimization criteria facilitating the CRONE design of controllers that are as robust and as efficient as possible have therefore been proposed. This paper proposes to optimize an additional design parameter that simplifies the choice of the required nominal model of the plant. A high dynamic Engine-Dynamometer test-bed MIMO control problem is used to show the efficiency of this modified third generation CRONE design.

This paper presents a methodology of robust control applied on a nonlinear MIMO system, on the air path of a turbocharged diesel engine. The methodology consists in first analyzing the MIMO system to observe dynamic properties with several tools, i.e. condition number, relative gain array and Gershgorin bands, before designing the controller. Hence, a sequential robust controller synthesis is proposed to obtain a decentralized control taking into account coupling and uncertainties of the nonlinear system. The results obtained from a Mean Value Engine Model (MVEM) engine simulation model show the real time applicability of the proposed method and the good control performances (good response time, no steady state error) for various engine speeds.

An extension to mxn multivariable (non-square multivariable) plants with time-delay of the CRONE control system design is presented. To avoid difficult design and implementation, this paper proposes the design of a robust decentralized controller based on the use of the block relative gain for the pairing of the manipulated inputs and controlled outputs. The main advantage of the proposed methodology is the ease of hand-tuning and also of understanding by non-specialist.

An extension to mxn multivariable (non-square multivariable) plants with time-delay of the CRONE control system design is presented. To avoid difficult design and implementation, this paper proposes the design of a robust decentralized controller based on the use of the block relative gain (BRG) for the pairing of the manipulated inputs and controlled outputs. The main advantage of the proposed methodology is to simplify the design of the controller by transformed the model of the system into a simplified model.

This article deals with the problem of the reduction of structural vibrations with isodamping property. The proposed methodology is based on: a contour defined in the Nichols plane and significant of the damping ratio of the closed-loop response and on a robust control method that uses fractional order integration. The methodology is applied to an aircraft wing model made with a beam and a tank whose different levels of fillings are considered as uncertainties.

This article deals with the vibration control of a MIMO plant. The plant under study is an aircraft wing model with a tank whose levels of filling may vary. The model is thus uncertain and a robust control is necessary to guarantee the performance of the closed-loop response. As the problem concerns vibration reduction, the method focuses on the robustness of the damping factor of the closed-loop response. The proposed methodology is based on: - a contour defined in the Nichols plane and significant of the damping factor of the closed-loop response - the CRONE control method that is a robust method based on fractional order integration.

This article deals with the reduction of structural vibrations. Two approaches are possible to tackle this problem, either a passive method with dampers, or an active method with actuators that are controlled in order to decrease or even cancel the vibrations in the structure. The second method is used here. The objective is to control the damping of plants that are not only lightly damped but also whose models are uncertain. The proposed methodology is based on iso-damping contours and CRONE control. The iso-damping contour is defined thanks to fractional order integration in the Nichols plane and is graduated with the value of the damping factor of the closed-loop response. The CRONE control is a robust control method that uses fractional order integration. The methodology is here applied to a multivariable plant that is an aircraft wing model made with a beam and a tank whose different levels of fillings are considered as uncertainties.

The control of time-delayed perturbed systems is easy when time delay affects system inputs or outputs. In the more difficult case when system states are affected, CRONE (fractional order) control-system design (CSD) methodology can be adapted and used. Stability analysis is achieved using interval analysis. An academic time-delayed system is used to illustrate the robust CSD methodology and the robust stability analysis. In order to provide a reduced-order robust controller, a reduced-order Pade approximation of the nominal system is selected as the nominal plant.

A robust controller design is proposed for the active suspension system bench-mark problem. The CRONE control system design used is extended to unstable multivariable plants with lightly damped modes and RHP zeros. Decoupling and stabilizing controller K, is achieved for the open-loop transfer matrix. Fractional order transfer functions are used to define all the components of the diagonal open-loop transfer matrix, β. In defining the fractional open-loop transfer function β0i some elements of the plants, G0 and its inverse must be considered to achieve the stable controller. Optimisation provides the best fractional open-loop βopt . Finally, frequency domain system identification is used to find controller K=G0 −1 βopt .Copyright © 2007 by ASME

International audience