Franck Guillemard

Lithium-ion batteries modeling

This paper deals with lithium-ion batteries modeling. From an electrochemical model available in the literature, several assumptions and simplifying hypotheses are proposed in order to get a simpler but accurate model. The obtained model is based on a fractional transfer function resulting in the resolution of a partial differential equation that describes the lithium ion diffusion inside the electrodes. The model involves only three parameters and a polynomial that fits the open circuit voltage of the battery. A method to estimate the model parameters and the polynomial is proposed. A single discharge test (constituted of several discharge steps) is required to operate the parameter estimation method. The accuracy for battery voltage prediction of the resulting model is evaluated with various tests. A simplified model is obtained from a lithium-ion battery electrochemical model.The proposed model is a single-electrode model.Fractional differentiation is used for a low number of parameters in the model.A relative error less than 0.5% on the voltage is obtained under various conditions.The model simplicity and accuracy are interesting for use in automobile BMS.

Fractional Models for Thermal Modeling and Temperature Estimation of a Transistor Junction

The thermal behavior of a power transistor mounted on a dissipator is considered in order to estimate the transistor temperature junction using a measure of the dissipator temperature only. The thermal transfers between the electric power applied to the transistor, the junction temperature, and the dissipator temperature are characterized by two fractional transfer functions. These models are then used in a Control Output Observer (COO) to estimate the transistor junction temperature.

CRONE Cruise Control System

This paper deals with vehicle longitudinal control performed by a cruise control (CC) system using the CRONE approach. A comparison between this approach, a classical proportional-integral (PI) controller, and an H-infini (Hinf) controller is presented. Simulations with these controllers are performed considering a complex vehicle model obtained from simulator software taking mass uncertainties, aerodynamic drag, gravity, and wind forces into account. This model also accounts for wheel dynamics with tire-road interactions that allow the analysis of the adherence effect. Results show better robustness to uncertainties with the second-generation CRONE controller, as already demonstrated with the CRONE suspension system and the CRONE ABS system.

Lithium-ion battery state of charge estimation using a fractional battery model

With the development of hybrid and electric vehicles, automobile battery management systems (BMS) play a key role for a safe and optimal use of the battery within the powertrain. These systems have to give critical information on state of health, state of charge and available power for example. The accuracy of the information manipulated by the BMS depends on the embedded battery model accuracy. In this paper, we present a new State Of Charge (SOC) estimation algorithm based on a fractional battery model, for use in real-time in an automotive BMS.

A Markov Decision Process-based approach for trajectory planning with clothoid tentacles

The work presented in this paper focuses on reactive local trajectory planning which plays an essential role for future autonomous vehicles. The challenge is to avoid obstacles in respect to road rules while following a global reference trajectory. The planning approach used in this work is the method of clothoid tentacles generated in the egocentered reference frame related to the vehicle. Generated tentacles in a egocentered grid represent feasible trajectories by the vehicle, and in order to choose the right one, we formulate the problem as a Markov Decision Process.

Simple and Robust Experiment Design for System Identification Using Fractional Models

This paper tackles the problems of simple and robust experiment design for system identification using elementary fractional models. It is based on a frequency domain approach and allows to determine the best sine input signal maximizing D-optimality criterion of the parameters inverse covariance matrix in different contexts? First, a single parameter (any of the parameters of the elementary fractional model) is assumed to be unknown. Next, any combination of two and then three parameters are supposed to be unknown. Finally, the problem of robust experiment design is treated when a bounded interval of the estimated parameters is known, in the same contexts.

Integrating safety distances with trajectory planning by modifying the occupancy grid for autonomous vehicle navigation

The goal of the work in this paper is to use occupancy grid in integrating safety distances with the planning strategy for autonomous vehicle navigation. The challenge is to avoid static and dynamic obstacles at high speed with respect to some specific road rules while following a global reference trajectory. Our local trajectory planning algorithm is based on the method of clothoid tentacles. It consists on generating clothoid tentacles in the egocentered reference frame related to the vehicle. Using information provided from sensors, we build an occupancy grid that we modify to take into consideration safety distances. We use this modified occupancy grid to classify each tentacle as navigable or not navigable. By formulating the problem as Markov Decision Process, only one tentacle among the navigable ones is chosen as the vehicle local reference trajectory.

Fractional Models of Lithium-Ion Batteries with Application to State of Charge and Ageing Estimation

The lithium-ion batteries are currently used for a wide variety of mobile applications due to their high energy/power density and operating voltage. However, they also suffer from some limitations that force car manufacturers to associate them to a Battery Management System (BMS) that diagnoses and control the battery pack in real time. To carry out an accurate battery diagnosis, the BMS uses models of each cell in the pack. In this paper a two fractional models of lithium-ion cell are proposed. They result from several simplifications of an electrochemical model involving several partial differential equations. The very low number of parameters in the simpler proposed model permits their adjustment with a very simple procedure. It is then shown how this model can be used for State of Charge (SOC) and ageing estimation. As due to ageing cell and model behavior mismatch, a solution is proposed to define if the model parameters adjustment is required.

Scene-aware driver state understanding in car-following behaviors

This research represents the heterogeneity in car following by a hidden variable driver state, which could change due to the drivers habit, fatigue, distraction, influence of surrounding traffic etc, resulting in the heterogeneous behaviors of such as fast or slow, strong or weak response to the same level of stimuli. A probabilistic method of driver state understanding is proposed by modeling and reasoning the heterogeneity in car-following behaviors, and the influence of surrounding traffic is addressed explicitly in addition to the leader-follower pair aiming at applications in crowded real-world traffic. Experiments are conducted by using the on-road trajectory data that were collected from motorways in Beijing, where four distinctive driver states and corresponding car-following models are learnt. With online understanding of driver state, the particular car-following model is used to predict the drivers velocity control, where results of improved accuracy are demonstrated.

Detection of Electric Contact Resistance Variations in Automotive Connectors

Car manufacturers have to size electric and electronic systems to avoid the risk of short circuits while, at the same time, ensuring a viable economic balance. In other words, the copper mass must be sufficient for safety reasons but not excessive for cost reasons. It is, thus, necessary to monitor the critical points of the electric architecture in order to make an appropriate decision to maintain a high level of safety. However, due to physical and economic constraints, direct temperature measurement of these critical points is seldom possible. Moreover, temperature monitoring at these points would not allow one to determine whether the rise in temperature was related to degradation of the contact or whether it was due to the generation of thermal power by another component. The objective of this paper is, thus, to propose a new method to monitor critical points of the electric architecture that does not require direct measurements. In order to achieve this objective, an electrothermal model of the architecture was developed, and a diagnosis method was used. The method was applied to detect abnormal variations in the contact resistance inside a connector, which is a critical point commonly encountered in the electrothermal chain of automotive vehicles. The efficiency of the algorithm was evaluated on a dedicated test bench. The proposed approach is able to detect a deviation of about 10% in the contact resistance, thus validating the proposed methodology.