Navigating battery aging: prolonging battery lifespan with AI
A thorough approach to managing battery health involves the improvement of temperature, charging practices, and implementation of advanced battery management systems (BMS) to enhance the longevity of the life of the battery. This includes maintaining an ideal operating temperature range, adhering to recommended charging practices, and utilising cutting-edge technologies (like ML and AI) to improve the battery's performance and extend its lifespan.
By following these best practices, businesses and individuals can ensure that their EV batteries (as well as others) remain in optimal condition, thereby reducing the need for unnecessary replacements and repairs, and ultimately saving time and money.
Understanding battery aging: key concepts and factors
Battery aging comprises capacity degradation and internal resistance increases to degradation rates, leading to reduced energy storage capacity and efficiency over time.
Any type of battery, regardless of state of charge (SOC) or its purpose (whether for a remote or an EV), experience aging. But what does this mean exactly?
Understanding the aging of batteries involves understanding two key elements of battery aging: the decline in capacity and internal resistance within the battery itself.
Capacity degradation & internal resistance degradation
Think of a water tank that gradually becomes full capacity and holds less and less water. This is similar to what happens with any battery when they go through capacity loss or degradation, where their ability to store electrical energy decreases over time. Various factors such as battery type, temperature, and charging patterns can impact this reduction in capacity.
As batteries age, their efficiency and power output decrease due to both battery degradation and capacity fade caused by a rise in internal resistance. This decline affects the performance of electric vehicles (EVs) and stationary energy storage systems, significantly limiting range and impacting overall battery operation. The gradual loss of battery capacity has implications for various applications reliant on them as an energy source.
The impact of temperature
The aging of batteries is also heavily influenced by temperature. Extreme heat, high temperatures, and cold can have detrimental effects on the health cycle life. Understanding these consequences enables us to take steps to maintain our batteries within the recommended temperature range, ultimately prolonging their longevity.
Lithium-ion battery life: how long will it last?
Using a widely used example, the lifespan of lithium-ion batteries is influenced by several factors such as design, usage, environmental conditions, power sources, and charging habits, all of which affect the behavior of lithium ions within the battery itself.
Li-ion batteries, also referred to as lithium batteries, play a significant role in our daily lives. Whether powering smartphones and laptops or being utilised in EVs, the duration of their life is a matter of curiosity. Determining the lifespan of lithium-ion batteries isn’t simple as it relies on various aspects of the battery's lifespan such as design, usage patterns, and environmental conditions that directly impact how these types of ions behave within these types of batteries.
Electric vehicle battery aging: what you need to know
As the global trend shifts towards more environmentally-friendly transportation options, EVs are gaining popularity. Yet, one of the major concerns surrounding EVs is how their batteries will perform in terms of health and longevity.
It is essential to explore and address the unique challenges that come with battery cell aging specifically in electric vehicles. This involves finding solutions to the aging mechanism to ensure optimal functioning and lifespan for these crucial components used in EVs’ operation.
Engineers have to navigate a complex set of competing objectives, such as satisfying regulatory mandates, meeting certification standards, and fulfilling customer expectations. Despite the availability of physics-based tools, these tools often struggle to identify the best possible solutions within the expansive design space. In this recent blog, we aim to find the best method for charging an electric vehicle (EV) battery in just ten minutes while maximising the battery's overall lifespan.
Innovations in battery management systems
As the battery ages and our dependence on them increases, the significance of efficient battery management systems (BMS) also rises. Creative BMSs have the potential to improve battery performance, delay aging processes, and extend life for longer with less energy usage.
The complexity of battery models and their sensitivity to various factors makes it necessary to use machine learning (ML) for optimising battery management systems. The availability of interchangeable physics and battery modeling libraries provides a vast amount of data for ML to analyse and optimise.
Moreover, advanced deep learning techniques can discover higher dimensional relationships that are challenging to parameterise, which further augments the existing battery information. By using machine learning approaches to battery modelling, it is possible to produce key battery diagnostics with relatively high accuracy and at an accelerated rate.
Battery data: turning insights into action
Utilising data is a valuable resource in comprehending battery capacity and maintaining battery well-being. Assessing this information yields an understanding of the battery’s capabilities, detects any problems that may arise during the battery's lifetime, and enables informed choices to extend its lifespan.
With the growing demand for energy storage, accurate battery models, risk analysis, and predictive analytics have become increasingly critical. Many industries are now using sensitivity analysis to enhance their precision models, scenario analysis, and predictive analytics to interpret their battery-captured data.
Battery lifetime and aging conclusion
Proper battery life health management includes maintaining a battery and/or battery pack at optimal temperatures, improving charging habits, and using advanced battery management systems to extend the battery’s life span.
To summarise, by knowing what impacts battery health and taking steps to reduce degradation, we can improve device efficiency and minimise harm to the environment.
The capabilities of Artificial Intelligence (AI) have vast implications for the global battery industry market. This technology can enable battery researchers to explore analytical relationships within the battery cell infrastructure. For instance, they can look at less charged cells or the most charged cells, which can aid companies in reducing the time taken to produce optimal-performing battery cells.