Méthodes d’optimisation dynamique de systèmes à plusieurs états pour l'efficacité énergétique automobile

Energy management system (EMS) for hybrid vehicles consists on determining the power split between the different energy sources in order to minimize the overall fuel consumption and/or pollutant emissions of the vehicle. The objective of this thesis is to develop an EMS taking into account the internal temperatures (engine temperature and/or catalyst temperature). In a first part and using a prior knowledge of vehicle driving cycle, the EMS design is formulated as an optimal control problem. Then, the PMP is used to solve this optimization problem. Based on the obtained numerical results, some trade-off between performance of the control strategy and complexity of the model used to calculate this strategy is established. The various problems studied in this thesis are examples of successive model simplifications which can be recast in the concept of regular perturbations in optimal control under input constraints discussed here. In a second part, the feedback law of ECMS is generalized to include thermal dynamics. This defines sub-optimal feedback strategies which we have tested numerically and experimentally.La gestion énergétique (EMS) pour véhicules hybrides a pour objectif de déterminer la répartition de puissance entre les différentes sources d'énergie de manière à minimiser la consommation de carburant et/ou les émissions polluantes. L'objectif de cette thèse est de développer un EMS en prenant en compte des températures internes (la température du moteur et/ou la température du système de post-traitement). Dans une première partie et en utilisant une connaissance préalable du cycle de conduite, le calcul d'un EMS est formulé comme un problème de commande optimale. Ensuite, le principe du minimum de Pontryagin (PMP) est utilisé pour résoudre ce problème d'optimisation.~En se basant sur les résultats numériques obtenus, un compromis entre les performances de la stratégie de commande et de la complexité du modèle utilisé pour la calculer est établi. Les différents problèmes étudiés dans cette thèse sont des exemples des simplifications successives de modèle qui peuvent être regroupées dans le concept des perturbations régulières en contrôle optimal sous contrainte de commande discuté ici. Dans une deuxième partie, la formulation de l'ECMS a été généralisée pour inclure les dynamiques thermiques. Ces extensions définissent des stratégies sous-optimales que nous avons testées numériquement et expérimentalement

Optimal Predictive Eco-Driving Cycles for Conventional, Electric, and Hybrid Electric Cars

International audienceIn this paper, the computation of eco-driving cycles for electric, conventional and hybrid vehicles using receding horizon and optimal control is studied. The problem is formulated as consecutive-optimization problems aiming at minimizing the vehicle energy consumption under traffic and speed constraints. The impact of the look-ahead distance and the optimization frequency on the optimal speed computation is studied to find a trade-off between the optimality and the computation time of the algorithm. For the three architectures considered, simulation results show that in urban driving conditions, a look-ahead distance of 300m to 500m leads to a sub-optimality less than 1% in the energy consumption compared to the global solution. For highway driving conditions, a look-ahead distance of 1km to 1.5km leads to a sub-optimality less than 2% compared to the global solution

Dynamic optimization in multi-states systems for automobile energy efficiency

La gestion énergétique (EMS) pour véhicules hybrides a pour objectif de déterminer la répartition de puissance entre les différentes sources d'énergie de manière à minimiser la consommation de carburant et/ou les émissions polluantes. L'objectif de cette thèse est de développer un EMS en prenant en compte des températures internes (la température du moteur et/ou la température du système de post-traitement). Dans une première partie et en utilisant une connaissance préalable du cycle de conduite, le calcul d'un EMS est formulé comme un problème de commande optimale. Ensuite, le principe du minimum de Pontryagin (PMP) est utilisé pour résoudre ce problème d'optimisation.~En se basant sur les résultats numériques obtenus, un compromis entre les performances de la stratégie de commande et de la complexité du modèle utilisé pour la calculer est établi. Les différents problèmes étudiés dans cette thèse sont des exemples des simplifications successives de modèle qui peuvent être regroupées dans le concept des perturbations régulières en contrôle optimal sous contrainte de commande discuté ici. Dans une deuxième partie, la formulation de l'ECMS a été généralisée pour inclure les dynamiques thermiques. Ces extensions définissent des stratégies sous-optimales que nous avons testées numériquement et expérimentalement.Energy management system (EMS) for hybrid vehicles consists on determining the power split between the different energy sources in order to minimize the overall fuel consumption and/or pollutant emissions of the vehicle. The objective of this thesis is to develop an EMS taking into account the internal temperatures (engine temperature and/or catalyst temperature). In a first part and using a prior knowledge of vehicle driving cycle, the EMS design is formulated as an optimal control problem. Then, the PMP is used to solve this optimization problem. Based on the obtained numerical results, some trade-off between performance of the control strategy and complexity of the model used to calculate this strategy is established. The various problems studied in this thesis are examples of successive model simplifications which can be recast in the concept of regular perturbations in optimal control under input constraints discussed here. In a second part, the feedback law of ECMS is generalized to include thermal dynamics. This defines sub-optimal feedback strategies which we have tested numerically and experimentally

Online Energy Management System (EMS) Including Engine and Catalyst Temperatures for a Parallel HEV

International audienceIn this paper, a first practical extension of the Equivalent Consumption Minimization Strategy (ECMS) is proposed to include thermal dynamics (engine and catalyst temperatures) in the optimal design of an Energy Management System (EMS) for a parallel Hybrid-Electric light-duty Vehicle (HEV). The task of this novel multi-state ECMS is to achieve a sufficient level of performance with respect to pollutant emissions while keeping fuel consumption within acceptable limits. The extension suggested here is based on correlations between the thermal state and their corresponding adjoint states, observed along extremal calculated from extensive offline solutions of optimal control problems. Simulation results stress that the obtained performance is sufficient to satisfy the environmental norms while keeping fuel consumption sub-optimality relatively marginal

Comparison of several strategies for HEV energy management system including engine and catalyst temperatures

International audienceIn this paper, we investigate the benefits of consid- ering advanced modeling of engine and after-treatment system (3-way catalyst) in the design of Energy Management System (EMS) for a parallel Hybrid-Electric light-duty Vehicle (HEV) (passenger car with gasoline engine). The evaluation is based on a comparative study of optimal control problems formulated using three distinct levels of model complexity. Starting with a single state dynamics (battery state-of-charge), successively, we consider the engine temperature and the 3-way catalyst temperature, yielding increased complexity. As is shown, the increased complexity brings only little improvement in fuel economy and emissions reduction. We provide quantitative results to assess this observation

On the impact of model simplification in input constrained optimal control: application to HEV energy-thermal management

International audienceIn this paper, we propose a result allowing to simplify the statement of input constrained optimal control problems. In details, it is shown that perturbation terms of magnitude ε appearing in the dynamics and the cost function can be neglected, because they only yield an improvement of magnitude ε2 in the optimal cost. This result, which is is handy for practical applications, is here proven by means of an interior penalty method to deal with input constraints. For illustration, an example of energy management system for a Hybrid Electric Vehicle (HEV) is treated. As is expected, the complexity of the problem can be reduced at very little expense of sub-optimality. Based on simulations, quantitative results in term of fuel consumption are provided

Optimal predictive eco-driving cycles for conventional and electric cars

International audienceIn this paper, the computation of eco-driving cycles for electric and conventional vehicles using receding horizon and optimal control is investigated. The problem is formulated as consecutive-optimization problems aiming at minimizing the vehicle energy consumption under traffic and speed constraints. The solving method is based on Dynamic Programming (DP). The impact of the look-ahead distance on the optimal speed computation is studied to find a trade-off between the optimality and the computation time. Simulation results show that in urban driving conditions, a look-ahead distance of 300m to 500m leads to a sub-optimality less than 0.6% in the energy consumption compared to the global solution. For highway driving conditions, a look-ahead distance of 1km to 2km leads to a sub-optimality less than 0.7% compared to the global solution

Numerical optimal control as a method to evaluate the benefit of thermal management in hybrid electric vehicles

International audienceIn this paper, a numerical solution of the optimal thermal management problem for a parallel hybrid electric vehicle is presented by taking into account the engine temperature. This temperature influences the fuel consumption and has a dynamical behavior which is controlled by the engine torque. Simulation results are presented to evaluate the benefit of adding this new state variable to the optimization problem, by comparison to the simplified problem where only the State Of Charge (SOC) is taken into account

Computation of eco-driving cycles for Hybrid Electric Vehicles: Comparative analysis

International audienceIn this paper, the calculation of eco-driving cycles for a Hybrid Electric Vehicle (HEV), using Dynamic Programming (DP), is investigated from the solving method complexity viewpoint. The study is based on a comparative analysis of four optimal control problems formulated using distinct levels of modeling. Starting with three state dynamics (vehicle position and speed, battery state-of-charge) and three control variables (engine and electric machine torque, gear-box ratio), the number of state variables is reduced to two in a first simplification. The other two simplifications are based on decou-pling the optimization of the control variables into two steps: an eco-driving cycle is calculated supposing that the vehicle is propelled only by the engine. Then, assuming that the vehicle follows the eco-driving cycle calculated in the first step, an off-line energy management strategy (torque split) for an HEV is calculated to split the requested power at the wheels between the electric source and the engine. As is shown, the decreased complexity and the * Corresponding author. decoupling optimization lead to a sub-optimality in fuel economy while the computation time is noticeably reduced. Quantitative results are provided to assess these observations

PROCEDE DE DETERMINATION D’UNE CONSIGNE DE VITESSE POUR MINIMISER LA CONSOMMATION ENERGETIQUE D’UN VEHICULE

L'invention porte sur un procédé de détermination d'une consigne de vitesse pour une chaîne de traction d'un véhicule, ledit procédé comprenant les étapes suivantes - la détermination (E2) d'une distance d'observation, désignée horizon électronique, inférieure à la distance totale, - la mise en oeuvre (E3) d'un premier algorithme de détermination d'un profil de vitesse maximale sur un tronçon considéré, jusqu'à l'horizon électronique, à partir de données issues d'au moins une source, - la mise en oeuvre (E5) d'un deuxième algorithme d'optimisation de la consommation énergétique pour déterminer un profil de vitesse optimale permettant de minimiser la consommation énergétique sur le tronçon considéré, jusqu'à l'horizon électronique, en fonction au moins du profil de vitesse maximale déterminée par le premier algorithme