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Mining in Canada stands as one of the most energy-intensive sectors, playing a pivotal role as a significant provider of copper, nickel, and cobalt to the international market. Anticipated growth in the global population, coupled with the transition of several low-income economies to middle-income status, is poised to escalate the demand for essential raw materials. This surge in demand is expected to drive an increase in energy consumption across various stages of the Canadian mining industry, encompassing exploration, extraction, processing, and refining. Due to their geographical constraints, most Canadian mining operations rely heavily on fossil fuels such as diesel and heavy fuel. Considering the global shift towards decarbonization and the pursuit of net-zero emission targets, exploring avenues for adopting electrification solutions and integrating renewable energy technologies, particularly in sizable surface mines, is imperative. Within this context, our study delves into the challenges and prospects associated with infusing renewable energy technologies and embracing electrification alternatives within Canadian mining practices. This exploration encompasses a comprehensive review of pertinent literature comprising academic research, technical analyses, and data disseminated by international entities and experts. The findings underscore a prevalent trend wherein Canadian mining enterprises are prominently investing in robust electric truck fleets, particularly for heavy-duty operations. Additionally, incorporating renewable energy solutions is notably prevalent in remote sites with extended operational lifespans. However, an in-depth examination reveals that the most formidable hurdles encompass successfully integrating renewable energy sources and battery electric vehicles. Financial constraints, logistical intricacies, and the imperative to enhance research and development competencies emerge as pivotal challenges that demand strategic addressing.

Fuel cell (FC) hybrid electric vehicles (HEVs) are currently drawing attention to reducing the astonishing reliance on fossil fuels and the amount of carbon dioxide emissions owing to their zero emissions and quick refueling time. Nonetheless, recreational three-wheel electric vehicles (EVs) are experiencing new challenges in their power electronics systems since they are restricted to limited spaces, high dynamic required powers, and long driving ranges. Thus, selecting the proper power electronic topology enables them to decrease the circuit complexity and requested space, extend the lifetime of the hybrid energy storage system (HESS) and enhance their performance. This can lead to more affordable EVs. In this sense, the use of a Zsource inverter topology integrating a new HESS and new semiconductor devices is critical to replace traditional two-stage inverters in these vehicles. This substitution requests an appropriate selection of passive components for the Z-source network (ZSN), a strict control approach, and an efficient energy management strategy (EMS). Considering the aforementioned aspects, this thesis puts forward a novel high-performance (HP) active switched quasi-ZSI (AS-qZSI) for the studied FC-HEV. Firstly, a framework based on the multi-criteria decision-making approach is employed to rank various ZSI topologies from the best topology to the worst one regarding the targeted operations and performances. Therefore, the AS-qZSI is chosen for the FC HEV. Secondly, the HP-AS-qZSI is figured out by substituting one normal capacitor in the ZSN with a lithium-ion capacitor (LiC) bank to reduce the passive components' size and volume. By adding an anti parallel power switching device into the ZSN of the AS-qZSI, the proposed HP-AS-qZSI is enabled to deal with distorted/uncontrollable dc-link voltages in a broad range of loads over the original AS-qZSI. Thirdly, an improved differential evolution (IDE)-based Linear–quadratic regulator (LQR) control, Les véhicules électriques hybrides (HEV) à pile à combustible (FC) attirent actuellement l’attention sur la réduction de la dépendance étonnante aux combustibles fossiles et de la quantité d’émissions de dioxyde de carbone en raison de leur absence d’émissions et de leur temps de ravitaillement rapide. Néanmoins, les véhicules électriques (VE) récréatifs à trois roues font face à de nouveaux défis en termes de systèmes électroniques de puissance, car ils sont limités à des espaces limités, à des puissances dynamiques élevées et à de longues autonomies. Ainsi, la sélection de la topologie électronique de puissance appropriée leur permet de réduire la complexité du circuit et l'espace requis, de prolonger la durée de vie du système de stockage d'énergie hybride (HESS) et d'améliorer ses performances. Cela peut conduire à des véhicules électriques plus abordables. En ce sens, l’utilisation d’une topologie d’onduleur à source Z intégrant un nouveau HESS et de nouveaux dispositifs semi-conducteurs est essentielle pour remplacer les onduleurs traditionnels à deux étages dans ces véhicules. Cette substitution nécessite une sélection appropriée de composants passifs pour le réseau de sources Z (ZSN), une approche de contrôle stricte et une stratégie de gestion énergétique efficace (EMS). Compte tenu des aspects susmentionnés, cette thèse propose un nouveau quasi-ZSI commuté actif (AS-qZSI) haute performance (HP) pour le FC-HEV étudié. Premièrement, un cadre basé sur une approche décisionnelle multicritère est utilisé pour classer les différentes topologies ZSI de la meilleure topologie à la pire en fonction des opérations et des performances ciblées. Par conséquent, l’AS-qZSI est choisi pour le FC-HEV. Deuxièmement, le HP-AS-qZSI est conçu en remplaçant un condensateur normal dans le ZSN par une batterie de condensateurs lithiumion (LiC) afin de réduire la taille et le volume des composants passifs. En ajoutant un dispositif de commutation de puissance anti-parallèle dans l

This article introduces a dynamic semiempirical model that predicts the degradation of a proton exchange membrane fuel cell (PEMFC) by introducing time-based terms in the model. The concentration voltage drop is calculated using a new statistical equation based on the load current and working time, whereas the ohmic and activation voltage drops are updated using time-based equations borrowed from the existing literature. Furthermore, the developed model calculates the membrane water content in the PEMFC, which indicates the membrane hydration state and indirectly diagnoses the flooding and drying faults. Moreover, the model parameters are optimized using a recently developed butterfly optimization algorithm. The model is simple and has a short runtime; therefore, it is suitable for monitoring. Voltage degradation under various loading currents was observed for long working hours. The obtained results indicate a significant degradation in PEMFC performance. Therefore, the proposed model is also useful for prognostics and fault diagnosis.

This paper puts forward an approach for boosting the efficiency of energy management strategies (EMSs) in fuel cell hybrid electric vehicles (FCHEVs) using an online systemic management of the fuel cell system (FCS). Unlike other similar works which solely determine the requested current from the FCS, this work capitalizes on simultaneous regulation of current and temperature, which have different dynamic behavior. In this regard, firstly, an online systemic management scheme is developed to guarantee the supply of the requested power from the stack with the highest efficiency. This scheme is based on an updatable 3D map which relates the requested power from the stack to its optimal temperature and current. Secondly, two different EMSs are used to distribute the power between the FCS and battery. The EMSs' constraints are constantly updated by the online model to embrace the stack performance drifts owing to degradation and operating conditions variation. Finally, the effect of integrating the developed online systemic management into the EMSs' design is experimentally scrutinized under two standard driving cycles and indicated that up to 3.7% efficiency enhancement can be reached by employing such a systemic approach. Moreover, FCS health adaptation unawareness can increase the hydrogen consumption up to 6.6%.

To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.

An energy management strategy (EMS) efficiently splits the power among different sources in a hybrid fuel cell vehicle (HFCV). Most of the existing EMSs are based on static maps while a proton exchange membrane fuel cell (PEMFC) has time-varying characteristics, which can cause mismanagement in the operation of a HFCV. This paper proposes a framework for the online parameters identification of a PMEFC model while the vehicle is under operation. This identification process can be conveniently integrated into an EMS loop, regardless of the EMS type. To do so, Kalman filter (KF) is utilized to extract the parameters of a PEMFC model online. Unlike the other similar papers, special attention is given to the initialization of KF in this work. In this regard, an optimization algorithm, shuffled frog-leaping algorithm (SFLA), is employed for the initialization of the KF. The SFLA is first used offline to find the right initial values for the PEMFC model parameters using the available polarization curve. Subsequently, it tunes the covariance matrices of the KF by utilizing the initial values obtained from the first step. Finally, the tuned KF is employed online to update the parameters. The ultimate results show good accuracy and convergence improvement in the PEMFC characteristics estimation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Battery energy storage and management systems constitute an enabling technology for more sustainable transportation and power grid systems. On the one hand, emerging materials and chemistries of batteries are being actively synthesized to continually improve their energy density, power density, cycle life, charging rate, etc. On the other hand, advanced battery management systems (BMSs) are being intensively developed to guarantee the safety, reliability, efficiency, and cost-effectiveness of batteries in realistic operations, as well as their integration with mechatronics. Owing to their multi-physics nature, designing high-performance batteries and their management systems requires multidisciplinary approaches, with an ever-increasing synergy of electrochemi- cal, material, mechatronics, computer, and control disciplines.

Recently, modular powertrains have come under attentions in fuel cell vehicles to increase the reliability and efficiency of the system. However, modularity consists of hardware and software, and the existing powertrains only deal with the hardware side. To benefit from the full potential of modularity, the software side, which is related to the design of a suitable decentralized power allocation strategy (PAS), also needs to be taken into consideration. In the present study, a novel decentralized convex optimization (DCO) framework based on auxiliary problem principle (APP) is suggested to solve a multi-objective PAS problem in a modular fuel cell vehicle (MFCV). The suggested decentralized APP (D-APP) is leveraged for accelerating the computational time of solving the complex problem. Moreover, it enhances the durability and the robustness of the modular powertrain system as it can deal with the malfunction of the power sources. Herein, the operational principle of the suggested D-APP for the PAS problem is elaborated. Moreover, a small-scale test bench based on a light-duty electric vehicle is developed and several simulations and experimental validations are performed to verify the advantages of the proposed strategy compared to the existing centralized ones.

This study investigates the impact of battery and fuel cell (FC) degradation on energy management of a FC hybrid electric vehicle. In this respect, an online energy management strategy (EMS) is proposed considering simultaneous online adaptation of battery and FC models. The EMS is based on quadratic programming which is integrated into an online battery and proton exchange membrane FC (PEMFC) parameters identification. Considering the battery and PEMFC states of health, three scenarios have been considered for the EMS purpose, and the performance of the proposed EMS has been examined under two driving cycles. Numerous test scenarios using standard driving cycles reveal that the ageing of battery and PEMFC has a considerable impact on the hydrogen consumption. Moreover, the proposed EMS can successfully tackle the model uncertainties owing to the performance drifts of the power sources at the mentioned scenarios.

This study proposes an energy management strategy (EMS) for a dual-mode hybrid locomotive equipped with a fuel cell, supercapacitors, and batteries, and intermittent access to an electrified overhead catenary. It is inspired by the Ragone plot and does not consider information or predictions of future load consumption. It aims to reduce a cost function that considers the cost of hydrogen, the electricity consumed from the network, and the energy sources' degradation. The EMS focuses on maximising the energy recovered during braking. The study introduces a methodology to tune the EMS parameters. Two study cases are used to evaluate the EMS. In the evaluation driving profile, typical for a French freight train, the braking energy is around 12.8% of the total energy. With the proposed EMS, the energy recovered is around 99.8% of the total braking energy. A second EMS not oriented to reduce the energy in the braking resistor is also evaluated. The energy recovered with this strategy is around 91.5% of the total braking energy. The global energy reduction is around 1.1% compared with the second EMS and 12.8% without energy recovering. These results show a real opportunity to increase the energy recovered during braking.

Demand Side Management Strategies (DSMSs) can play a significant role in reducing installation and operational costs, Levelized Cost of Energy (LCOE), and enhance renewable energy utilization in Stand-Alone Microgrids (SAMGs). Despite this, there is a paucity in literature exploring how DSMS affects the planning of SAMGs. This paper presents a methodology to design an incentive-based DSMS and evaluate its impact on the planning phase of a SAMG. The DSMS offers two kinds of incentives, a discount in the flat tariff to increase the electrical energy consumption of the users, and an extra payment added to the fare to penalize it. The design of the methodology integrates the optimal energy dispatch of the energy sources, the tariff design, and its sizing. In this regard, the main contribution of this paper is the design of an incentive-based DSMS using a Disciplined Convex approach, and the evaluation of its potential impacts over the planning of SAMG. The methodology also computes how the profits of the investors are modified when the economic incentives vary. A study case shows that the designed DSMS effectively reduces the size of the energy sources, the LCOE, and the payments of the customers for the purchased energy.

The low economy of fuel cell hybrid electric vehicles is a big challenge to their wide usage. A road, health, and price-conscious optimal cost minimization strategy based on decision making framework was developed to decrease their overall cost. First, an online applicable cost minimization strategy was developed to minimize the overall operating costs of vehicles including the hydrogen cost and degradation costs of fuel cell and battery. Second, a decision making framework composed of the driving pattern recognition-enabled, prognostics-enabled, and price prediction-enabled decision makings, for the first time, was built to recognize the driving pattern, estimate health states of power sources and project future prices of hydrogen and power sources. Based on these estimations, optimal equivalent cost factors were updated to reach optimal results on the overall cost and charge sustaining of battery. The effects of driving cycles, degradation states, and pricing scenarios were analyzed.

Active configuration i.e., source coupling via a power converter, is the most common configuration for fuel cell/supercapacitor (FC/SC) vehicles. Passive connection of the FC with the SCs without any converters is an original and less expensive solution to distribute the power among the sources. This passive configuration does not require an energy management strategy. In fact, the power distribution only depends on the FC and SC impedance characteristics. Conventional methods to size the SC follow two criteria: storage capacity and maximum voltage. In this paper, a third criterion is added which is the FC operating current dynamics. This novel sizing methodology reduces the FC degradation and improves the global system efficiency. Experimental results provide validation to the proposed sizing approach. The SCs boost the FC to meet the requirements of the load with a guarantee of system stability reaching higher global performances and less stress to the FC.