Break-free from current norms of designing and controlling Li-ion battery systems
This post is created by Puneet Sinha.
Designing and developing a system with Li-ion batteries is like solving a puzzle. You have pieces (Li-ion cells in this case) but how are you going to put them together and how are you going to allow them to operate to the maximum potential without sacrificing life or safety within the physical constraints is the name of the game for system engineers. Essentially, Li-ion battery system engineering demands a robust balance among electrical engineering (electrical energy interaction with other system components), chemistry (Li-ion cell materials dictate life and safety), and mechanical engineering (thermal management).
System engineers across the world are relying on system-level software to design and optimize Li-ion battery systems for their products. But is the commonly used system software approach sufficient to address the challenges of this evolving industry? Most of the system engineers will say, No! Most commonly, empirical softwares are used for system engineering that requires a lot of experimental data under wide range of condition to curve fit. Such software tools are rigid and don’t allow system engineers to innovate, beyond pre-determined constraints, that is needed to deliver winning products in the market. At EC Power, we have, after understanding the challenges faced by system engineering and advanced engineering groups of a wide range of companies internationally, has developed new software, AutoLion-ST to eliminate the current limitations of Li-ion battery system engineering. Here are few ways of how AutoLion-ST is empowering users to break-free from current norms of product development:
1. Life and safety conscious system operating strategy
Empirical system simulation tools cannot account for the impact of cell operating strategy on its internal behavior, forcing very conservative operating algorithms. For instance, at present a majority of Li-ion battery charging protocols consists of charging at a certain current till a pre-determined voltage followed by charging at constant voltage (CCCV). Such protocols are built on certain rule of thumbs that are supposed to (but not necessarily proven) prevent Li plating, a detrimental phenomenon that can lead to unsafe event and fast life decay, during charging. These protocols typically allow very small charging current and force long charging time. But empirical system software can’t determine if for different cell designs or cell chemistry such CCCV protocols can actually prevent Li-plating. AutoLion-ST, on the other hand, allows system engineers to develop new algorithms that can not only charge batteries faster but also enable to do so safely and robustly. Life and safety of a Li-ion battery is governed by phenomenon at micro-scale of Li-ion battery material. AutoLion-ST gives users freedom to put direct control on such life and safety dictating variables and opens up numerous innovation opportunities.
2. Life-cost optimization
Typically, system developers take a very conservative approach of over sizing the system to ensure product warranty. Though practical, not only this approach incurs more cost, it makes system development extremely challenging for applications where space limitations are severe, such as automotive and consumer electronics. System developers while using empirical software cannot evaluate the impact of their operating strategy on system life and have to depend on time consuming and very costly testing-only approach. AutoLion-ST allows system developers to quickly and reliably evaluate impact of operation on life under real world drive cycles. This empowers users to correctly size a system considering degradation and develop optimized controlling algorithms, delivering ultimate life-cost optimization to their end product.
3. Make system design part of conversation from the get go
Empirical system models, by their nature, force system engineers to come to the table only when the batteries are selected for a product program. Given the pressure to reduce time to market, there is an increasing need from system engineering/advanced engineering teams to conduct trade-off studies among various energy storage units (Li-ion battery with other energy sources) and other components. This becomes critical for applications such as 48V micro hybrid, Fuel cell electric vehicle, plug-in hybrids and micro grid applications, AutoLion-ST enables engineering teams effectively conduct electrification system architecture selection and thereby leveraging wide supplier base to get the most suited system components that includes Li-ion batteries.
4. Quickly adapt to changes in development cycles
Transport electrification and renewable energy storage has great market demand. But R&D costs, testing and the constantly evolving requirements of customers are expensive and difficult to keep fulfilled. Especially when evolving Li-ion chemistries are chasing an evolving technology in a rapidly evolving market. Customer specifications and/or product requirements may change and system design and development needs to fulfill that in quick fashion. Commonly used empirical system software is unable to address this (they will need data from new cell to curve fit!!). Instead, engineers need powerful system software that can allow them to evaluate the impact of changes in cell design or chemistry on system operation quickly and reliably. With AutoLion-ST, system engineers can change cell design, chemistry or any other specification on the fly and accurately evaluate its impact on their system operation. AutoLion-ST is the system software that empowers system engineers to keep pace with constantly evolving product development in a time and cost-effective manner.
5. Add new capabilities without losing the advantages of empirical system softwares
One of the main reasons physics-based models are not commonly used by system engineering groups is due to their slow computational speed compared to empirical models. AutoLion-ST with its advanced algorithms eliminates this reservation. It delivers similar computational efficiency to users as that of empirical models but a wide range of flexibility in exploring design and controls algorithms. The software has minimal learning curve and is built to keep a user, who doesn’t necessarily know what is inside Li-ion battery, in mind.
To get a free trial version of AutoLion-ST, please contact us at email@example.com