Vehicle electrification increases the fuel efficiency of the transportation sector while lowering emissions. Eventually, however, electric vehicle batteries will reach their end-of-life (EOL) point, when the capacity of the battery is insufficient for operating a motor vehicle. At this point, the battery is typically removed for recycling. This treatment of the electric vehicle battery is not efficient, as there is still a high enough storage capacity that they can be used in various non-vehicular uses. Unfortunately, there are numerous barriers limiting the adoption of re-used electric vehicle batteries. Herein, the authors analyze the limitations and current codes and standards that affect re-purposed battery pack designs. Utilizing these requirements, a bench test setup is designed and built, to determine feasibility of a repurposed electric vehicle (EV) battery for stationary energy storage in Canada.

An accurate and computationally efficient lithium-ion battery model is beneficial when developing state-of-charge (SOC) and state-of-health (SOH) algorithms for battery management systems (BMS). These models allow for software-in-the-loop (SIL) and hardware-in-the-loop (HIL) testing, where the battery pack is simulated in software. However, development of these battery models can be time-consuming, especially when trying to model the effects of temperature and SOC on the equivalent circuit model (ECM) parameters. Estimation of this relationship is often accomplished by carrying out many experiments, which can be costly and time consuming for BMS manufacturers. To address these issues, this paper makes two contributions to literature. First, a comprehensive battery model is developed, where the ECM parameter surface is generated using a design of experiments (DOE) approach. Second, replication runs are conducted to accurately estimate the measurement noise and determine which model parameters are significant. The technique is then compared with existing approaches from the literature, and it is shown that, by using the proposed method, the same degree of accuracy can be obtained while requiring significantly fewer experimental runs. This can be advantageous for BMS manufacturers that require a high-fidelity model but cannot afford to carry out many experiments.

In the workplace, safety must be the first priority of all employers and employees alike. In order to maintain the safety and well-being of their employees, employers must demonstrate due diligence and provide the appropriate safety training to familiarize employees with the hazards within the workplace. Although, a student “project team” is not a business, the work done by students for their respective teams is synonymous with the work done in a place of business and thus requires that similar safety precautions and training be administered to students by their team leads and faculty advisors. They take on the role of supervisors within the team dynamic. Student teams often utilize the guidelines and policies that their universities or colleges have developed in order to build a set of standard operating procedures and safety training modules. These guidelines aid in providing a base for training for the team, however, they are no substitute for training specific to the safety risks associated with the work the team is doing. In order to comply with these requirements, a full analysis of the workplace is required to be completed. A variety of safety analysis techniques need to be applied to define the hazards within the workplace and institute appropriate measures to mitigate them. In this work, a process is developed for establishing a safety training program for a student project team, utilizing systems safety management techniques and the aspect of gamification to produce incentives for students to continue developing their skills. Although, systems safety management is typically applied to the design of active safety components or systems, the techniques for identifying and mitigating hazards can be applied in the same fashion to the workplace. They allow one to analyze their workplace and determine the hazards their employees might encounter, assign appropriate hazard ratings and segregate each respective hazard by their risks. In so doing, safety level assignment can be completed to ensure team members are trained to be able to work on the systems associated with a given risk level.