This paper presents a compact multi-physical model for lithium-ion batteries used in electric vehicles (EVs). The proposed framework combines an equivalent circuit for electrical behavior, a lumped thermal model, and a semi-empirical ageing model separating calendar and cycling effects. The model is parameterized and validated using experimental data from Kokam NMC-based High Energy (HE) and High Power (HP) cells. Results show high accuracy in voltage, temperature, and degradation prediction, with relative errors below 2%. The model structure offers a good balance between accuracy and computational cost, making it suitable for EV performance evaluation, ageing prediction, and battery management system integration.

In this research, we develop a thermal energy storage system utilizing phase change materials (PCM) to integrate in electric vehicles (EVs). This system is designed to provide heating for the passenger compartment during winter by integrating it into the existing heat pump in order to reduce the energy consumption of the compressor, which draws power from the vehicle’s battery pack. The design draws inspiration from the compact plate-fin heat exchanger, where the air passages are filled with PCM and the system is fully sealed. Due to the low thermal conductivity of the PCMs, aluminum fins are used as heat transfer technique. The main target of this article is to analyze the thermal behaviour of the system under different flow conditions, and to optimize the fin pitch and fin height in the system as a function of power requirements. The results showed that an efficient fin design enhances the heat transfer by 7.5 times between the PCM and the heat transfer fluid within the storage system.

This paper focuses on the optimization of the sizing of the on-board storage system in an electric vehicle. The source studied is composed of a combination of two Li-ion battery technologies (a high-power density battery and another high energy density). The interest of this hybridization will be illustrated by comparing the performance of this solution with that of a conventional source (high power battery). A study on the various possible hybridizations is detailed. Following this study, a report is drawn up on the interest of each hybridization according to constraints related to the type of mission, desired autonomy, weight, volume and lifespan of the storage system. The conclusion of this work led us to the need for a very precise choice of the auxiliary storage system. The latter must ensure sufficient autonomy to respect the constraints linked to the aging of the source.

Nowadays, electric vehicles represent one of the most significant chances to reduce the pollution production rate. Unfortunately, in electric motors, the efficiency decreases by the relationship between speed proposed by the driver and the torque required by the vehicle. Those parameters can be estimated in order to make an efficiency optimization based on present and future road/weather conditions. Regrettably, this kind of control (optimal control) requires a model with low compilation time. Since bicycle motorcycle has nonlinearities, in this article, a state reduced linear dynamic model able to reproduce the behavior of a TWEV by more than one minute will be proposed. The model is oriented to an optimal controller in energetic field, for this reason, the most significant states are longitudinal speed to be used with the input torque to calculate the efficiency of the electric motor and the Yaw angle to creates constraints over the trajectory that has to be covered. After the model is proposed, its accuracy is tested by a comparison with a numerical iteration software. Finally, a sensitivity test is made in order to determine the behavior of the error according to the friction coefficients of the rear and front pneumatics.

The aim of this paper is to develop multi-physical model to validate the performance on power management strategies developed in our laboratory. The different parts of this model (electrical, thermal and ageing models) will be described and validated using experimental results. In our case, the hybrid energy storage system is composed with two Li-ion cells, High energy modules and high power modules. The obtained results prove the good modelling of the two technologies with just 2% of error between the experimental data and the model data.

This paper deals with a global study of numerical control implementation applied to a DC-DC buck converter with two techniques, classical control technique (PI control) and robust control technique (H-infinity loop-shaping control). The H-infinity loop-shaping control is applied to improve the performance and the stability robustness of this power converter based on pulse-width-modulation (PWM) techniques. The experimental results are very promising. They show that H-infinity loop-shaping control performs better than PI control. H-infinity loop-shaping control reject disturbance and noise produce by the DC-DC power converter. In addition to experimental validation, the other added value of this paper is to demonstrate the feasibility of easily implementing robust numerical controls allowing rejecting disturbances without real impact on computing time, which is very important for embedded power converter applications.

Electric vehicles (EVs) are a step toward ecologic transportation and carmakers should improve their attractiveness. The energy storage system represents a huge piece of the total EV price and can reach 45%. Moreover, the battery has a limited lifespan that could be considered as insufficient (around five years) against an equivalent thermal vehicle. The aim of this paper is to study battery ageing to find a way to improve battery life and then make the EV more economically attractive. The study is here applied to the category of light commercial vehicles (LCV) used in a professional context. This category are limited to 3.5t. The electric energy storage system ages depending on the use but also when the component is not used. Customers' usages have been recorded with a specific tool and a model of the entire vehicle including a multi-physical battery model with ageing were done in order to predict customers' needs. Calendar and cycling degradations of battery cell are modeled based on literature and identified from experimental results. Finally, charging strategies are developed and its impacts are studied in order to improve battery lifespan.

The energy required by a two wheels electric vehicle (TWEV) to complete a trip is lower than common electric cars or internal combustion vehicles. However, there are considerable losses along the electric driving chain. Those losses added to a limited energy storage cause an impact over the TWEV autonomy. This appears to be the main factor, which limits the large-scale market penetration of TWEV. This paper aims to analyze the multiphysic behavior of the complete power-chain in order to study its effect on its energetic losses. Even when many dynamics model oriented to hardware design approach can represent the come multiphysic behavior of one or two elements of the power train, the approach proposed in this paper presents a balanced representation of all power chain able to be used in real-time optimization. This study will help to improve the capabilities of an onboard TWEV efficiency estimator system which uses a longitudinal force model. As a conclusion, the error of autonomy estimation is compared with thermal considerations and without them according to different operating points.

The design of mechatronic systems requires the collaboration between different engineers at the disciplinary level and multidisciplinary design optimization (MDO) in the system level. However, the lack of a common knowledge basis between the system and disciplinary levels creates a gap between them. Therefore, collaborative decision-making and optimization of the global system became complex and time-consuming. This paper focuses on an innovative approach that uses knowledge management (KM) and graph theory techniques to support complex mechatronic systems design and optimization. A demonstrator is developed and applied to an industrial use case to optimize an Electronic Throttle Body (ETB).

[email protected] has appeared as a new paradigm for continuously monitoring software systems execution to enable self-adaptation. This adaptation happens whenever a change, a failure or a bug is introduced within the execution environment. It is done by a causal bidirectional connection between design and execution artifacts supported by feedback-loop information. We developed an approach to integrate a secure lightweight dynamic adaptation of access control policies when new security requirements are introduced at runtime. The proposed runtime adaptation is supported by a fast checking of design models at runtime against security constraints. A vehicle-2-x security case study is used to demonstrate the benefits of our approach.

In this paper, we present a comparative study of four voting algorithms for two Induction Motor drive fault tolerant control to speed sensor failure schemes. In both Output and Input Fault Tolerant controller, the voting algorithm chooses the most appropriate output signal to ensure the best behavior in degraded mode. The performances are evaluated through simulations of a 7.5kW Induction Motor drive with robustness testing against parametric variations, as well as under load testing. The results show that Euler, Newton-Raphson and Maximum Likelihood voting algorithms are more efficient than the Weighted Average in both Fault Tolerant Control schemes.

This paper presents a vehicle transmission simulator coupled to a longitudinal vehicle dynamic model. The transmission simulator uses electric actuators to reproduce the mechanical characteristics of a real vehicle engine and its transmission chain. The developed approach allows to validate transmission and vehicle dynamic studies (control of automatic or robotized gearboxes, test of heat engine, dynamic behavior and passenger comfort...) without need to the real transmission system and the real environment of the vehicle. The proposed system is used to carry out a vehicle automated driving in the case of a car- following operation.