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Battery Design for Electric Vehicles

Key Takeaways

  • How to model batteries with electrochemistry and equivalent circuits.

  • Some equivalent battery circuits lack temperature and SoC detail.

  • How sub-modeling better captures response through atomization.

View of car battery pack against a white background.

Battery design for electric vehicles requires appropriate modeling of the various performance metrics affecting the service life.

Rechargeable batteries have shaped the landscape of consumer products to an incalculable degree over the past decades. A desire for portability and concern over traditional battery waste/replacement has touched nearly every market sector and created brand-new ones. Now battery technology is facing its magnum opus in portability: the automobile. Electric engines continue to improve and challenge the internal combustion engine’s market dominance, yet current battery constraints remain a bottleneck. Innovative battery design for electric vehicles must grow correspondingly to push forward.

Equivalent Circuits Model Battery Design for Electric Vehicles

Battery design for electric vehicles begins with modeling in two forms: electrochemistry and equivalent circuits. The detail of the former is beyond the scope of this article: it concerns static models of the physical characteristics of the battery while utilizing finite element analysis to study the electrochemical interactions throughout the different battery regions. While electrochemical models are fundamental for this subject, they offer little insight into the dynamic performance of the battery across the range of operating conditions. Modeling batteries as lumped element circuits allows for a more expressive interaction between the designer and the simulation, which can further develop into the electrical circuitry that operates within and alongside the battery.

Comparing Equivalent Battery Circuit Models





Requires only two values (resistance and current/voltage) to describe.

Overly simplified.
Lacks physical parameters.


Introductory model to batteries that includes capacitance and network polarization based on the direction of current (charge/discharge).

No temperature-dependence. Less applicable to electric batteries than more specific topologies.


Incorporates the battery’s steady state and transient response with capacitance as its defining trait.

No temperature-dependence. Requires nesting of RC circuits to simulate better response, which may require higher order differential equations to solve.


Splits circuit into its constituents to better approach each individually.

Cohesive response has to be pieced together from individual sub-models SoC and SoH require curve fitting.

Most people’s first experience with network analysis treats a battery as a voltage source and nothing more. While useful as a teaching tool, this idealized form does not represent real-world performance. Even more precise equivalent circuit models like Thevénin and Norton that add resistance to the voltage source are not detailed enough for high-power battery applications. Specifically, these equivalent circuits fail to account for changes to the circuit’s operation based on temperature, state of charge (SoC), and other physical parameters that alter the battery's performance.

Battery circuit modeling can start with the schema developed for lead-acid batteries. Although it’s not directly applicable to electric batteries, it provides a great jumping-off point for deeper analysis. Lead-acid equivalents somewhat resemble the Norton model (parallel resistance) but add branches with diodes for the charging and discharging direction. The most considerable improvement with this approach is the addition of temperature-dependent resistance and capacitance values from empirically fitting data with a least square curve. Still, the lead-acid model cannot account for SoC, limiting its usefulness and applicability.

A more appropriate model emulates the electric battery with a network of resistors and capacitors. The advantage of modeling with capacitors instead of voltage sources is the dynamic response of the capacitors during steady-state conditions. Depending on the amount of stored charge, a capacitor is more likely to present as an open or short circuit to the current flow, meaning the circuit's topology evolves predictably throughout its charge/discharge cycles. A further refinement distributes the capacitance between a bulk capacitor that reflects the total storage of the battery and a smaller yet responsive charge/discharge capacitor. 

Divide-and-Conquer Modeling Methods

There is no universal equivalent model for electric batteries, and considering the various technologies and electrochemistry, there’s a case that it’s better to adapt modeling techniques to fit the battery than vice versa. For the many variables present in an equivalent circuit across its operating range, even a singular model fit to the parameters of a specific battery can be challenging. Investigating the major performance areas as sub-models heuristically offers an excellent middle-ground between a thorough treatment and feasibility:

  • Main circuit - The open circuit voltage uses a dependent voltage source to underline the relationship between temperature, SoC, and the battery state of health (SoH). The model includes branches for the charging and discharging directions, which feature RC networks to reflect the time-variant nature of the steady state and the multiple speeds of transient signals. 

  • SoC and SoH - The state models are independent but closely related: SoC will decrease during discharge cycles, but SoH will decrease over the battery's life due to nonregenerative material wear. Due to its temporal nature, the SoC can vary throughout usage, but the maximum SoC heavily depends on the SoH. As the battery's health degrades, so does its storage capacity and ability to hold a charge.

  • Thermal - Modeling thermal circuits is essential for understanding the electronic performance and is often used at the device level to determine the viability of thermal conduction and convection routing. Here, the sub-model treats the source as a power generator based on the instantaneous I-V characteristics and considers the power dissipated across the battery's bulk resistance (temperature-dependent). The battery and system voltage capacitance replaces with heat capacity and temperature.

Developing equivalent circuit sub-models requires sophisticated numerical approaches, even split into their respective domains. Specifically, SoC and SoH present difficulties in predicting the wear on a battery, yet the success of electric battery storage relies on monitoring degradation to combat performance loss and extend the service life. Long-term battery viability depends on the ease of modularity within these approaches, so continued efforts to improve the general applicability of these models are ongoing.

Cadence Solutions Help Drive the Future

Battery design for electric vehicles encompasses many fields and disciplines to maximize energy storage performance, reliability, and safety. Significant market penetration of the electric car comes on the heels of advancements in battery technology. Yet, battery capabilities still face additional hurdles to better adoption rates. Keys to furthering the technology rely on continued research and development with modeling that dramatically accelerates the pace of design and production. Cadence understands the value of modeling in ECAD: our suite of PCB Design and Analysis Software aids design teams with sophisticated circuit methods. Simulation results are rapidly integrable into OrCAD PCB Designer for a seamless transition to a layout that fosters productivity during tight production schedules.

Leading electronics providers rely on Cadence products to optimize power, space, and energy needs for a wide variety of market applications. To learn more about our innovative solutions, talk to our team of experts or subscribe to our YouTube channel.