Feasibility Study of Current and Emerging Battery Chemistries for Electric Vertical Take-Off and Landing Aircraft (eVTOL) Applications

Abstract

The feasibility of electric vertical take-off and landing aircraft (eVTOL) relies on high-performance batteries with elevated energy and power densities for long-distance flight. However, systemic evaluation of battery chemistries for eVTOLs remains limited. This paper fills this research gap through a comprehensive investigation of current and emerging battery technologies. First, the properties of current battery chemistries are benchmarked against eVTOL requirements, identifying nickel-rich lithium-ion batteries (LIB), such as NMC and NCA, as the best suited for this application. Through comparison of 300 commercial battery cells, the Molicel INR21700-P45B cell is identified as the best candidate. Among next-generation batteries, SiSu solid-state batteries (SSBs) emerge as the most promising alternative. The performance of these cells is evaluated using a custom eVTOL battery simulation model for two eVTOL aircraft: the Volocopter VoloCity and the Archer Midnight. Results indicate that the Molicel INR21700-P45B underperforms in high-load scenarios, with a state of charge (SoC) at the end of the flight below the 30% safety margin. Simulated SoC values for the SiSu cell remain above this threshold, reaching 64.9% for the VoloCity and 64.8% for the Midnight. These results highlight next-generation battery technologies for eVTOLs and demonstrate the potential of SSBs to enhance flight performance.

1. Introduction

Climate change poses significant risks to people and the environment, emphasizing the need for prompt action to mitigate its impact. A key to address this challenge is to reduce greenhouse gas (GHG) emissions across all industries. In 2023, the transport sector alone was responsible for approximately 8 Gt CO_2eq GHG emissions, corresponding to about 15% of the total global GHG emissions [1]. Of these, approximately 426 Mt CO_2eq were generated by the aviation sector, with an increase of 23% relative to the year 2021 [1]. Although this currently accounts for only 3% of the current global GHG emissions, projections indicated that emissions could triple by the year 2050 if current fuels remain in use as a result of increased air traffic [2]. To address these challenges, current research is focusing on the transition of the aviation sector toward more sustainable propulsion technologies. A promising approach is the use of hydrogen fuel cells, which offer high gravimetric energy density and rapid refueling times [3]. However, their adoption faces significant challenges, such as the space constraints of high-pressure hydrogen storage systems and the limited power density of fuel cells, which affect their suitability for high-velocity, long-range aviation. An alternative is the employment of sustainable aviation fuels (SAFs), such as plant-based biofuels, synthetic fuels, and hydrogenated vegetable oils (HVO) [4]. These fuels are already employed together with conventional jet fuels in existing commercial aircraft. However, current SAF production is limited to less than 1% of global aviation fuel demand, with challenges including high production costs and feedstock availability [4]. Finally, electric aviation is gaining traction for short-haul and urban air mobility applications, thanks to advancements in lithium-ion battery (LIB) technology, which provides high power density [5].

In recent years, this has opened the door to a new generation of electric aircraft, such as drones and light sport aircraft, and spurred the development of new types of vehicles, such as electric vertical take-off and landing aircraft (eVTOL). Similarly to helicopters, eVTOLs are able to depart and land vertically in limited spaces [6], while causing much less noise and air pollution. These features make them well suited for applications such as air taxis, agriculture or emergency medical vehicles [6]. Additionally, eVTOLs can travel up to 6 times faster than terrestrial vehicles [7], offering a valid solution to alleviate traffic congestion in urban and metropolitan areas [8]. This use case is known as urban air mobility (UAM) [9]. A practical example of this use case is demonstrated by Joby Aviation, which envisions using eVTOLs to connect New York JFK Airport to central Manhattan in just 7 min, compared to a 49-min car journey (More information available at https://www.jobyaviation.com/, accessed on 3 February 2025).

Currently, several global original equipment manufacturers (OEMs) are actively developing eVTOLs. Despite their progress, eVTOL design presents several challenges, especially due to the strict requirements on battery performance. High battery capacity is required to enable long-distance flight, while high power output is needed for the take-off and landing phases. These demands, coupled with the limited available space aboard the aircraft, mean that batteries with high gravimetric energy density and power density are needed to make eVTOL flight feasible. Furthermore, batteries must meet specific safety regulations, which are very strict compared to those for electric vehicle (EV) batteries [8], as outlined by organizations such as the European Aviation Safety Agency (EASA) [10].

Although high-performance batteries are crucial for eVTOL design, there is only limited research addressing the specific battery requirements for this specific application. For example, [11] provides an overview of battery chemistries suited for electric aviation. However, it does not address the specific requirements of eVTOLs. The study compares LIBs with nickel–cadmium (Ni–Cd) and lead-acid batteries, both of which are no longer widely used in most mobility application. Additionally, the analysis overlooks the significant performance differences among various LIB chemistries. In [8], battery requirements for eVTOLs are identified and experimental tests are conducted on two LIB cells. However, this study mainly emphasizes fast charging capabilities, whereas other important performance metrics, such as the gravimetric energy density, are overlooked. Similarly, [12] describes some key performance metrics for eVTOL batteries. However, the study does not clarify explicit minimum threshold values for the gravimetric energy density and power density to enable eVTOL flight. Additionally, it does not provide simulation or experimental data about the battery performance during flight to support the findings. Likewise, [13] highlights the limitations of existing electrochemical energy storage systems for eVTOL but fails to specify any requirement for this application. This clear lack of guidelines highlights a gap in the current research and complicates the selection of optimal battery chemistries for this application, making it also challenging to identify suitable emerging technologies to enhance eVTOL performance.

To address the identified research gap, this paper provides a comprehensive analysis to establish the battery requirements for eVTOLs, focusing on technical feasibility. Therefore, the gravimetric energy density and power density are identified as the key requirements to ensure flight with a representative profile while maintaining a battery state of charge (SoC) above a 30% safety threshold. Minimum requirement values for these parameters are identified for two distinct eVTOL models: the VoloCity, a lightweight, wingless vehicle from the OEM Volocopter, and the Midnight, a heavy vectored thrust aircraft from the OEM Archer. Based on these requirements, an extensive evaluation of both current and emerging battery chemistries is conducted to determine the best suited candidates for this application. The findings are verified via simulation using a custom-developed eVTOL simulation model. Based on this, key performance metrics, such as the state of charge (SoC), the discharge current, and the battery voltage are simulated for both battery chemistries to assess their viability.

This paper is structured as follows. In Section 2.1, the main battery requirements to enable eVTOL flight are determined using mathematical models. In Section 2.2, the main current and emerging battery chemistries are benchmarked against the requirements and the most suitable candidates are identified. The suitability of the selected battery cells is then verified in Section 3 via the developed simulation model, which is introduced in Section 2.3. The conclusions and an outlook on future work are finally provided in Section 4.

2. Materials and Methods

2.1. Requirements Analysis

The availability of technical data regarding commercial eVTOLs is often limited due to confidentiality. Therefore, in this paper, parameters such as energy, power, and SoC are derived based on mathematical models and publicly disclosed aircraft specifications. When specific data are not available, estimations are used.

It is important to note that the method and equations presented in Section 2.1.2 apply to all propeller-based eVTOLs. These include both wingless architectures (e.g., the Volocity multicopter from Volocopter) and fixed-wing designs, such as heavy vectored thrust architectures like the Archer Midnight. However, they are not well-suited for ducted vectored thrust eVTOLs, such as the Lilium Jet, due to their distinct propulsion system [14].

2.1.1. Flight Profile

The battery requirements for eVTOL application vary depending on the specific flight profile. This includes information about the overall distance and duration of the individual flight phases [15]. Each of these phases is characterized by different performance and power requirements [8]. Since most OEMs do not disclose this information, in this paper, a eVTOL flight profile consisting of five phases is adopted in this paper to identify realistic battery requirements.

Table 1. Custom eVTOL flight profiles including the Volocopter VoloCity and the Archer Midnight.

Phase	Velocity ${\mathit{v}}_{\mathit{p}\mathit{h}\mathit{a}\mathit{s}\mathit{e}}$ (m/s)		Duration Tphase (s)
	Volocity	Midnight
Initial hovering	-	-	5.0
Take-off	3.0	3.0	60.0
Cruise	28.0	66.0	600.0
Descent	3.0	3.0	60.0
Landing hovering	-	-	5.0
Total flight	-	-	730.0

shows the flight profile for the two considered eVTOL models: the Volocopter Volocity and the Archer Midnight. The same profile is shown graphically in Figure 1.

The first flight phase is the initial hovering phase and typically only lasts a few seconds. This phase is required for controlled take-off in confined areas, such as rooftops and designated landing zones. The subsequent take-off phase involves vertical climbing at a constant velocity between 2.5 to 3.6 m/s for most eVTOLs [16]. In this paper, a vertical climb velocity of 3 m/s for a duration of 60 s is assumed to achieve an altitude of 180 m. This altitude is sufficient for urban travel applications, as the minimum flight height for UAM is 122 m [17]. The cruise phase is conducted at constant altitude and velocity, allowing the aircraft to reach its destination. The cruise velocity differs for the two considered eVTOL models and it is 28 m/s for the Volocopter VoloCity (More information available at: https://evtol.news/volocopter-volocity/, accessed on 3 February 2025), and 66 m/s for the Archer Midnight (More information available at: https://evtol.news/archer/, accessed on 3 February 2025). In this paper, the duration of the cruise phase is set to 10 min. The following descent phase lasts 60 s with a descent velocity of 3 m/s, followed by the landing hovering phase with a duration of 5 s. During this last phase, the aircraft performs precise control adjustments for directional steering and stabilization.

The total flight duration is 730 s, covering a distance of approximately 17.2 km for the Volocity and 40 km for the Midnight. This distance remains within the maximum operational range of each aircraft (20 km for the Volocity (more information available at: https://www.volocopter.com/en/solutions/volocity, accessed on 3 February 2025), and 80 km for the Midnight (more information available at: https://archer.com/aircraft, accessed on 3 February 2025), making it a realistic flight scenario.

2.1.2. Power and Energy Demand for eVTOL Flight

In this section, the power and energy demand is computed for each phase of the flight profile described in Section 2.1.1. The overall energy demand can be determined as:

$$E_{tot}=E_{hover}+E_{take-off}+E_{cruise}+E_{descent}+E_{landing},$$

(1)

where E_hover, E_take-off, E_cruise, E_descent and E_landing are the energy demands during the initial hovering, take-off, cruise, descent, and landing hovering phases, respectively. For each phase, the energy demand can be calculated as:

$$E_{phase}=P_{phase}·T_{phase},$$

(2)

where P_phase is the power demand and T_phase the phase duration.

Initial Hovering Phase

The power demand in the initial hovering phase is computed [18] as:

$$P_{hover}={\displaystyle \frac{MTOW·g}{n_h}}·\sqrt{{\displaystyle \frac{MTOW·g}{a_w·p·A_r}}},$$

(3)

where MTOW is the maximum take-off weight of the aircraft, equal to the sum of the aircraft weight and its payload, g is the gravitational constant of the earth, and n_h is the hovering efficiency of the aircraft. This parameter quantifies the ability of the aircraft to maintain a stationary position in the air relative to the energy or power required. It is influenced by factors such as rotor blade design, aerodynamic efficiency, blade surface characteristics, and overall system losses within the aircraft. Its value typically lies between 0.6 and 0.7 for most eVTOLs. The parameter a_w accounts for the contraction of the wake behind a rotor system in hovering or vertical flight and equals 2 for open propellers, such as the ones employed in eVTOLs [18]. The air density p is 1.2 kg/m³, whereas the total rotor area A_r is calculated for open propellers as:

$$A_r=x_p·\pi ·r_p^2,$$

(4)

where x_p is the number of propellers and r_p the radius of the propeller.

Take-Off Phase

The power required for vertical flight during the take-off phase is determined as [19]:

$$P_{\mathit{take-off}}=P_{hover}·{\displaystyle \frac{v_{\mathit{take-off}}}{2{\upsilon }_I}}+\sqrt{{\left({\displaystyle \frac{v_{\mathit{take-off}}}{2{\upsilon }_I}}\right)}^2+1},$$

(5)

where v_take-off is the climb velocity and is shown in Table 1. The induced velocity $\upsilon$_I represents the difference between the average rotor inflow and outflow velocity and is computed as [20]:

$${\upsilon }_I=\sqrt{{\displaystyle \frac{MTOW}{2·p·A_r}}}.$$

(6)

Cruise Phase

The power demand during the cruise phase is computed as [18]:

$$P_{cruise}={\displaystyle \frac{MTOW·g·v_{cruise}}{E_R·n_c}},$$

(7)

where E_R is the lift-to-drag ratio. This parameter measures the aerodynamic efficiency of the aircraft and indicates how much lift it generates relative to the aerodynamic drag. Its value typically lays between 4 and 15 [18]. The parameter v_cruise is the cruise velocity and n_c denotes the cruise efficiency, which quantifies how effectively an aircraft maintains level flight at cruise speed while minimizing energy consumption. The value of this parameter varies between 50% and 60% depending on the aircraft design [18].

Descent Phase

The power demand P_descent during the descent phase is typically the same as the power demand during the initial hovering phase [19].

Landing Hovering Phase

The power demand P_landing during the landing hovering phase is typically the same as the power demand during the take-off phase [8].

Table 2. Technical parameters of Volocopter VoloCity and Archer Midnight.

Parameter	Symbol	Unit	VoloCity	Midnight
Maximum take-off weight	MTOW	kg	900.0	3175.0
Number of propellers	xp		18.0	12.0
Propeller radius	rp	m	1.2	0.9
Total rotor area	Ar	m2	74.8	30.5
Lift-to-drag ratio	Er		3.5	11.3
Hover efficiency	nh		0.7	0.7
Cruise efficiency	nc		0.5	0.5
Cruise velocity	vcruise	m/s	28.0	66.0

lists the value of the parameters in Equations (3)–(7) for the Volocopter VoloCity and the Archer Midnight [16]. Most of the listed values are provided by the manufacturers. The values of the hover and cruise efficiencies are estimated from [18], whereas the lift-to-drag ratios of the Archer Midnight are derived from technical data released by the manufacturers (More information available at: https://www.aopa.org/news-and-media/all-news/2023/february/pilot/future-flight-archer-aviation, accessed on 3 February 2025). For the Volocopter Volocity, this value is derived from [18], which specifies the lift-to-drag ratio for multicopter eVTOL architectures.

Based on the values listed in Table 1 and Table 2, Equations (2)–(7) are used to compute the power and energy demand for each flight phase. These are listed in

Table 3. Power demand of Volocopter VoloCity and Archer Midnight.

Phase	Symbol	Unit	VoloCity	Midnight
Initial hovering	Phover	kW	88.5	917.3
Take-off	Ptake-off	kW	165.7	1149.9
Cruise	Pcruise	kW	141.3	395.5
Descent	Pdescent	kW	88.5	917.3
Landing hovering	Planding	kW	165.7	1149.9

and

Table 4. Energy demand of Volocopter VoloCity and Archer Midnight.

Phase	Symbol	Unit	VoloCity	Midnight
Initial hovering	Ehover	kWh	0.1	1.3
Take-off	Etake-off	kWh	2.8	19.2
Cruise	Ecruise	kWh	23.5	65.9
Descent	Edescent	kWh	1.5	15.3
Landing hovering	Elanding	kWh	0.2	1.6
Total flight	Eflight	kWh	28.1	103.3

, respectively, together with the total energy demand during the flight. Notice that optimal environmental conditions (e.g., absence of wind) are assumed for the calculation. Also, additional power consumption from the auxiliary systems (e.g., heating and lighting) is not considered in this paper.

2.1.3. Battery Requirements for eVTOL Application

In this section, the battery requirements for eVTOL application are determined based on the energy and power demand computed in Section 2.1.2.

Gravimetric Energy Density

To enable eVTOL flight, the state of charge (SoC_EoF) of the battery at the end of flight must be sufficiently high to allow eventual emergency maneuvers, as well as to avoid excess current spikes [8], which can cause battery overheating and dangerous thermal events. In this paper, a minimum allowable SoC of 30% at the end of flight is considered [21]. Based on this value, the minimum allowable gravimetric energy density ED_min of the employed battery cells is determined as:

$$E{D}_{min}={\displaystyle \frac{E_{flight}}{m_{C,tot}·(1-So{C}_{EoF})}},$$

(8)

where m_C,tot is the total mass of the cells contained in the battery pack. This value can be derived as a fraction of the mass m_B of the battery pack, which includes both the battery cells and additional components, such as the cables, the thermal management systems, the housing, and other structural elements. In most EV batteries, the ratio between m_C,tot and m_B is between 0.55 and 0.75 [8]. In this paper, an average value of 0.65 is considered and m_C,tot is derived as:

$$m_{C,tot}=0.65·m_B.$$

(9)

Since most OEMs do not disclose the value of m_B, in this paper it is estimated as [14]:

$$m_B=0.3·MTOW.$$

(10)

Table 5. Estimated battery pack and total cell mass of Volocopter VoloCity and Archer Midnight.

Parameter	Symbol	Unit	VoloCity	Midnight
Battery pack mass	mB	kg	270.0	952.5
Total cell mass	mC,tot	kg	175.5	619.1

lists the values of m_B and m_C,tot for the Volocopter VoloCity and the Archer Midnight.

The values of ED_min are listed for the two considered eVTOL models in

Table 6. Minimum required gravimetric energy density and power density for the Volocopter VoloCity and the Archer Midnight.

Parameter	Symbol	Unit	VoloCity	Midnight
Minimum cell gravimetric energy density	EDmin	Wh/kg	238.1	240.9
Minimum cell power density for take-off	PDmin	W/kg	944.0	1857.0

. For ease of comparison, an energy density of 240 Wh/kg is set as a requirement in this paper.

Power Density

As seen in Table 3, the power demand for eVTOLs is typically highest during the take-off and landing hovering phases. Based on this, the minimum allowable cell power density PD_min can be computed as:

$$P{D}_{min}={\displaystyle \frac{P_{\mathit{take-off}}}{m_{c,tot}}}.$$

(11)

Notice from Equation (5) that this value is dependent on the climb velocity. Considering a climb velocity of 3 m/s [16], the values of PD_min are listed in Table 6 for the Volocopter VoloCity and Archer Midnight. Notice that the required power density is much higher for the Archer Midnight mostly due to its higher MTOW. For ease of comparison and to account for the increasingly steeper requirements for eVTOLs in terms of allowable payload, a power density of 2000 W/kg is set as requirement in this paper.

Other performance metrics, such as the charging C-rate and the cycle life, are crucial to evaluate the suitability of the battery for a specific application. High charging C-rates, for instance, reduce the aircraft downtime enabling multiple flights per day, while long cycle life extends battery usability. These factors have a significant economic impact and are typically considered in battery selection. However, this paper exclusively focuses on technical feasibility and therefore prioritizes gravimetric energy density and power density as primary benchmarking parameters.

2.2. Benchmark Analysis

In this section, both current and emerging battery chemistries are evaluated against the requirements identified in Section 2.1.3 to identify the most suitable candidates for eVTOL application.

2.2.1. Benchmark Analysis of Current Battery Chemistries

Most eVTOL OEMs do not disclose information regarding employed battery chemistries. Therefore, in this paper, the main LIB chemistries used in EVs are considered, and their properties are compared to the identified requirements, as shown in

Table 7. Comparison of current battery chemistries with eVTOL requirements [22,23,24,25].

Chemistry	Gravimetric Energy Density (Wh/kg)	Power Density (W/kg)
Lithium titanate oxide (LTO)	60–110	1000–10,000
Lithium iron phosphate (LFP)	90–160	1000–3000
Lithium manganese iron phosphate (LMFP)	120–180	1000–3000
Lithium manganese oxide (LMO)	100–150	1000–3000
Lithium nickel cobalt aluminum oxide (NCA)	200–260	800–2000
Lithium nickel cobalt manganese aluminum oxide (NCMA)	200–250	800–2000
Lithium nickel manganese cobalt oxides (NMC)	150–220	800–2000
Requirement for eVTOL	240	2000

. Notice that chemistries with nickel-rich cathodes (such as NMC, NCA, and NMCA) best fit the requirements in terms of gravimetric energy density and power density [22,23,24,25]. However, these battery types suffer from low thermal properties due to the high reactivity of nickel, which may represent a concern for application in eVTOL.

Depending on the specific application, battery cells based on the same chemistry are often customized to achieve different performance characteristics in terms of energy and power density [26]. Due to these significant differences, this paper analyzes several commercial cells to identify the best candidates for eVTOL application. This is achieved by means of an open-source database from the Fraunhofer Institute featuring 300 cylindrical battery cells with their technical data, such as dimensions, mass, capacity, voltage, and charge/discharge C-rates (More information available at: https://www.isi.fraunhofer.de/de/blog/themen/batterie-update/lithium-ionen-batterien-open-source-datenbank-veroeffentlicht.html, accessed on 3 February 2025). Only cylindrical cells are considered in this paper, as they best fit the safety requirements as provided in the regulations of the EASA [10]. The cells in the database are benchmarked against the gravimetric energy density and power density requirements, as shown in Figure 2. Notice that only one battery cell (Molicel INR21700-P45B) meets the requirements. This cylindrical cell features a nickel-based cathode chemistry, with its key technical parameters detailed in

Table 8. Technical parameters of Molicel INR21700-P45B.

Parameter	Unit	Value
Gravimetric energy density	Wh/kg	242.0
Power density	W/kg	2300.0

.

2.2.2. Benchmark Analysis of Emerging Battery Chemistries

Several innovative battery chemistries are currently under development and testing for applications such as stationary storage systems [27] and EVs [28]. In this section, the properties of these emerging chemistries are benchmarked against the identified requirements to identify the best candidates for eVTOL application. The following chemistries are considered.

Magnesium-Ion Batteries (MIB)

MIBs offer the potential for higher gravimetric energy than that of current LIBs [29]. They are also characterized by good safety characteristics, as magnesium is less prone to dendrite formation than lithium, reducing the risk of short-circuit and thermal runaway. However, they suffer from slow ion diffusion kinetics, resulting in reduced power density and limited charging and discharging C-rates [30].

Zinc-Ion Batteries (ZIB)

ZIBs are attracting attention due to their low manufacturing costs due to the higher abundance of zinc compared to lithium. However, these batteries are characterized by reduced gravimetric energy and power densities compared to LIBs [31].

Aluminum-Ion Batteries (AIB)

Similarly to ZIBs, AIBs are economical due to abundance of aluminum compared to lithium. Although this chemistry shows very high theoretical power density up to 1200 W/kg, the gravimetric energy density is typically lower than that of LIBs [32].

Sodium-Ion Batteries (SIB)

SIBs are characterized by high sustainability and low manufacturing costs due to the abundance of sodium [33], as well as long cycle life and high thermal stability. However, they show low energy density compared to LIBs [31,32].

Lithium-Sulfur Batteries (Li-S)

Li-S batteries are characterized by a lithium metal anode and a sulfur-based cathode [34]. These batteries offer a very high theoretical gravimetric energy density and the potential for lower material costs due to the abundance of sulfur. However, they face challenges such as high self-discharge and limited power density. Additionally, issues like the polysulfide shuttle effect, volume expansion of sulfur, and dendrite growth at the lithium anode contribute to capacity fade and safety concerns, making them less reliable for applications requiring consistent and long-term energy storage [35].

Metal-Air Batteries (MABs)

MABs employ oxygen from the air for the reactant, eliminating the need for a cathode and enabling very high gravimetric energy densities [31]. The anode is typically manufactured out of pure metal, such as lithium or zinc. These batteries are very promising due to their high energy density [36] and low costs. Their main disadvantage is that they cannot be recharged and the anode needs to be swapped when fully oxidized [37].

Solid-State Batteries (SSBs)

SSBs typically employ two metallic electrodes and a solid electrolyte, resulting in larger C-rates, higher safety, and improved thermal stability in comparison to LIBs. The properties of SSBs largely vary depending on the material used for the electrolyte and the electrodes.

• Oxide electrolyte solid state (OESS) batteries employ lithium lanthanum zirconium oxide and exhibit high ionic conductivity, resulting in C-rates up to 4C [38]. However, these batteries suffer from high interfacial resistance between the electrolyte and electrodes, which can limit their performance.
• Sulfide electrolyte solid state batteries with lithium anode (LiSu) use a lithium metal anode, a sulfide-based solid electrolyte, and nickel-rich cathodes such as NMC or NCA [39]. A significant challenge in their development is the formation of thick electronically insulating layers, which increase the internal resistance [39].
• Sulfide electrolyte solid state batteries with silicon anode (SiSu) also employ NMC or NCA for the cathode, together with a sulfur-based solid electrolyte and a silicon-based anode [39]. This configuration enables high gravimetric energy density up to 480 Wh/kg, as well as a charging C-rate up to 2C [39].
• Polymer electrolyte solid state batteries (LiPo) combine a lithium metal anode, a solid polymer electrolyte, and an LFP cathode. The main challenge of this technology lies in the low charging rate capabilities [39].

Table 9. Technical parameters of emerging battery chemistries [27,28,29,30,31,32,34,35,36,37,38,39].

Battery Chemistry	Gravimetric Energy Density (Wh/kg)	Power Density (W/kg)
Magnesium-ion (MIB)	80–120	100–300
Zinc-ion (ZIB)	50–120	30–150
Aluminum-ion (AlB)	40–220	>3000
Sodium-ion (SIB)	200	300
Lithium-sulfur (Li-S)	550	<500
Lithium-air	3460	<1000
Zinc-air	2790	<1000
Oxide electrolyte solid state (OESS)	320–400	480
Sulfide electrolyte, lithium anode solid state (LiSu)	340	<700
Sulfide electrolyte, silicon anode solid state (SiSu)	300–480	1500
Polymer electrolyte solid state (LiPo)	300	300
Requirement for eVTOL	240	2000

lists the technical parameters of the discussed emerging battery chemistries. Since most of these chemistries are still under research, many of the provided values are based on estimates and are subject to change as the technologies continue to advance. Notice that SiSu batteries are identified as the most suitable option for eVTOL application due to the combination of high gravimetric energy density and power density.

2.3. eVTOL Battery Simulation Model

This section presents the simulation model developed to assess the performance of the battery chemistries identified in Section 2.2 for application in eVTOLs. A schematic representation of the model is shown in Figure 3.

The main goal of the model is to simulate the battery performance for flight operation. Therefore, the model excludes additional electrical loads, such as the heating and ventilation systems, lights, and cockpit instruments. The input of the model is the power demand for each phase, which is computed via Equations (3)–(7) based on the technical parameters of the aircraft (see Table 2) and the flight profile defined in Section 2.1.1. For the Molicel INR21700-P45B, the cell input data are sourced from the built-in library of the MathWorks Simscape environment, which was used for modeling and simulation. Only the discharge voltage curves were directly derived from the manufacturer’s data sheet. For the SiSu cell, its characteristics were determined based on data from the Fraunhofer Institute [40]. As output, the battery voltage, current, SoC, and C-rate are simulated throughout the flight. The battery model includes the battery cells connected in series and parallel and is generated using the Simscape Battery Builder application. Further details about the model are provided in Appendix A.

To evaluate the performance for different architectures, two distinct eVTOL aircraft are simulated: the Volocopter VoloCity and the Archer Midnight. These vehicles are selected for their contrasting configurations, with the VoloCity being a lightweight, wingless vehicle, and the Midnight being a heavy vectored thrust aircraft. For each aircraft, two simulations are conducted, each using a different battery cell. The first simulation, discussed in Section 3.2, employs the Molicel INR21700-P45B cell presented in Section 2.2.1 and shows the limitations of current battery chemistries for eVTOL application. To overcome these drawbacks, Section 3.4 presents the simulation results using a custom solid-state SiSu battery cell, highlighting the potential of these chemistries for eVTOL application.

Battery Parameters

This section presents the parameters of the battery cells and battery packs employed for the simulation model.

Battery Cell Parameters

For the model, technical parameters such as the mass, the nominal voltage, the nominal capacity and the internal resistance of the cells are required. This information is available for the Molicel INR21700-P45B cell and is summarized in

Table 10. Estimated cell parameters for the Molicel INR21700-P45B cell and the SiSu cell.

Parameter	Symbol	Unit	INR21700-P45B	SiSu
Mass	mC	kg	0.07	0.07
Nominal voltage	VC	V	3.6	3.6
Nominal capacity	Cnom	Wh	16.2	33.6
Maximum internal resistance	R0	mΩ	13.8	13.8

.

Since solid-state SiSu cells are still under research and not available on the market, only limited information is known regarding their properties. Therefore, in this paper, the same mass is adopted for the custom SiSu cell employed for simulation and the Molicel INR21700-P45B cell. Additionally, a high gravimetric energy density of 480 Wh/kg is considered [40], resulting in a nominal capacity of 33.6 Wh. Finally, the same internal resistance and nominal voltage are considered for the two cells. This is because the ionic conductivity of the sulfide-based electrolyte employed in SiSu cells is very close to that of the liquid electrolyte used in the Molicel INR21700-P45B cells [41]. Additionally, SiSu cells employ high-nickel cathodes, similar to those in Molicel INR21700-P45B cells. The technical parameters of the two cells are listed in Table 10.

To account for the variations in the required discharging C-rate between the take-off and cruise phases, a dynamic resistance is included in the model. The value of this resistance for the Molicel INR21700-P45B cell is derived from the discharge curves provided by the cell manufacturer. Due to the aforementioned chemical similarities, the same value is adopted for the SiSu cell.

Battery Pack Parameters

Most eVTOL OEMs do not disclose information regarding the battery architecture. Therefore, in this paper, the number of series and parallel connections in the battery is estimated based on the available information regarding the aircraft and the battery cells.

Both the Volocopter VoloCity and the Archer Midnight employ several battery packs. The number of series connections N_S in each pack can be determined as:

$$N_S={\displaystyle \frac{V_B}{V_C}},$$

(12)

where V_B is the battery pack voltage. In this paper, V_B is set to 800 V for both eVTOLs, consistent with the voltage specification reported for the Archer Midnight (More information available at: https://www.ainonline.com/news-article/2022-11-18/archer-details-motor-and-battery-design-midnight-evtol-air-taxi, accessed on 3 February 2025). The number of parallel connections N_P can be determined as:

$$N_P={\displaystyle \frac{N_{cells}}{N_S·N_B}},$$

(13)

where N_B is the number of battery packs and N_cells the total number of battery cells. This can be estimated as:

$$N_{cells}={\displaystyle \frac{m_{C_{tot}}}{m_C}},$$

(14)

where m_C,tot is estimated from the aircraft MTOW using Equations (9) and (10). The number of battery packs is set to 11 for the Volocopter VoloCity and 8 for the Archer Midnight, resulting in a 222S1P configuration for the VoloCity and 222S5P for the Midnight. The simulation parameters of the battery packs are listed in

Table 11. Estimated battery pack parameters for the Volocopter VoloCity and the Archer Midnight.

Parameter	Symbol	Unit	Volocopter VoloCity	Archer Midnight
Total mass of the cells	mC,tot	kg	175	619
Number of battery packs	NB	-	11	8
Battery pack voltage	VB	V	800	800
Number of cells	Ncells	-	2442	8800
Number of series connection	NS	-	222	222
Number of parallel connection	NP	-	1	5

, while the resulting battery capacity C_B is shown for both aircraft and cell types in

Table 12. Estimated battery capacity C_B for the Volocopter VoloCity and the Archer Midnight by using the Molicel INR21700-P45B and SiSu battery cells.

Battery Cell	Unit	Volocopter VoloCity	Archer Midnight
Molicel INR21700-P45B	kWh	39.6	143.9
SiSu	kWh	84	297.1

.

3. Discussion

In this section, the simulation results are presented for the representative flight and both the Volocopter VoloCity and the Archer Midnight. The simulations are run by using first the Molicel INR21700-P45B cell and then the SiSu cell.

3.1. Power Demand

Figure 4 shows the power demand computed via Equations (3)–(7) for both eVTOL models during the flight. The five flight phases, as outlined in Table 1, are clearly visible and numbered as (1) initial hovering phase, (2) take-off phase, (3) cruise phase, (4) descent phase, and (5) landing phase. The maximum power demand is 165.7 kW for the Volocopter VoloCity and 1149.9 kW for the Archer Midnight. This significant difference is mainly due to the higher MTOW of the Midnight. Notably, the power demand of the Archer Midnight decreases by approximately 65.6% to 395.5 kW when transitioning from the take-off to the cruise phase. This is due to the wing-based design of this aircraft, which enables better lift generation during the cruise phase [14]. In contrast, the power demand of the Volocopter VoloCity decreases by only approximately 14.7% to 141.3 kW. For this aircraft, an additional power reduction to 88.5 kW can be noticed during the final hovering phase and it is due to the high operational efficiency of the wingless multi-copter architecture during hover maneuvers [14].

3.2. Simulation Results with Molicel INR21700-P45B Cell

Figure 5 shows the simulated battery current, voltage, and SoC during the flight. For both eVTOL models, the battery voltage decreases at the start of the take-off phase in response to the sudden current increase. Subsequently, the voltage decreases gradually as the discharge current continues to increase and the battery depletes. As a result, the current required at landing is higher than at take-off to maintain the same output power. This can be critical at the end of the flight, as large amounts of current must be drawn from the battery to deliver the required power, increasing the likelihood of battery damage and accelerated aging. Additionally, safety hazards may arise due to the increased internal resistance of the battery at low SoC, which can lead to elevated cell temperatures and a higher risk of thermal runaway.

At the end of the flight, the simulated SoC is 28.7% for the VoloCity and 27.5% for the Midnight. These values are slightly lower than the minimum allowable SoC of 30% specified in Section 2.1.3. The presented results align with findings from other research in the field of eVTOLs. For example, [42] simulated the SoC of a custom eVTOL battery using cells with an energy density of approximately 130 Wh/kg, resulting in an end-of-flight SoC below 20% for an eVTOL model with an MTOW of 2000 kg and a flight duration of 2100 s. A more detailed comparison is not feasible due to the lack of available information regarding power demand and the number of cells used in the battery pack.

Although these results correspond to a limiting case, where maximum MTOW and velocity are considered, they indicate that the Molicel INR21700-P45B cell may not reliably ensure safe operation under high-load, high-velocity conditions. This issue is further exacerbated by the fact that the simulation does not account for energy demands from auxiliary systems, such as lights and the battery cooling system, nor does it consider performance degradation due to battery aging. These findings highlight the need for battery cells with higher performance to enable the operation of eVTOLs under high-energy-demand scenarios.

3.3. Plausibility of the Simulation Results

Direct validation of the simulation results is not feasible due to the lack of experimental data on eVTOL battery performance from OEMs. To ensure plausibility, the simulated value of SoC_EoF is compared with a theoretical estimation derived from the eVTOL energy consumption and battery capacity:

$$So{C}_{EoF,est}=1-{\displaystyle \frac{E_{flight}}{C_B}},$$

(15)

where E_flight is calculated from Equation (1) and C_B is the total battery capacity (see Table 12). The deviation between the estimated and simulated value is calculated via the relative error $\delta$:

$$\delta ={\displaystyle \frac{So{C}_{EoF}-So{C}_{EoF,est}}{So{C}_{EoF,est}}}\times 100\%.$$

(16)

The values of SoC_EoF, SoC_EoF,est, and $\delta$ are listed in

Table 13. Comparison of SoC_EoF obtained from the simulation model with the values calculated with Equation (15).

eVTOL	SoCEoF	SoCEoF,est	$\mathit{\delta }$
Volocopter Volocity	28.7%	29.0%	1.2%
Archer Midnight	27.5%	28.2%	2.5%

for both eVTOLs. Notice that the simulated values closely align with theoretical expectations, with a relative error of 1.2% for the Volocopter Volocity and 2.5% for the Archer Midnight. These small deviations may be due to decrease in the cell capacity during flight as a result of increasing discharge current, which is not considered in Equation (15). Overall, these results confirm that the model correctly represents battery discharge trends during flight.

3.4. Simulation Results with SiSu Cell

As discussed in Section 2.2.2, solid-state batteries (SSBs) have the potential to deliver higher energy and power density compared to current LIBs. These attributes make SSBs highly promising for eVTOL application, potentially overcoming the performance limitations outlined in Section 3.2. Therefore, in this section, the performance of the two eVTOL models is simulated using a solid-state SiSu battery cell.

Figure 6 shows the discharge current (a,b), voltage (c,d), and SoC (e,f) of the two eVTOLs throughout the flight. Notably, the high gravimetric energy density of the SiSu cell results in a high remaining SoC at the end of the flight, reaching 64.9% for the Volocopter VoloCity and 64.8% for the Archer Midnight. Additionally, the voltage decreases more gradually compared to the Molicel INR21700-P45B cell, leading to up to 9% lower discharge currents at the end of the flight.

Figure 7 shows SoC_EoF for the two aircraft models using the Molicel INR21700-P45 cell (orange column) and the custom SiSu cell (blue column). These results clearly indicate that solid-state battery cells, such as those based on SiSu chemistry, offer significant better performance for eVTOL applications compared to current commercial LIBs, such as the Molicel INR21700-P45B cell.

3.5. Battery Thermal Sensitivity

As this paper focuses on the technical feasibility of batteries for eVTOL applications, thermal effects are not discussed in detail. However, it must be noted that high temperatures play a critical role in battery operation and safety. Nickel-based chemistries, such as those used in Molicel INR21700-P45B, are particularly sensitive to high temperatures, which can cause cell degradation and increase the risk of thermal runaway [43]. In contrast, solid-state batteries (such as SiSu batteries) show improved thermal stability due to their solid electrolyte, which reduces heat generation and minimizes the risk of thermal runaway. However, research indicated that prolonged exposure to high temperatures can degrade the electrolyte [44], increase the internal resistance [45], and induce mechanical stress [46], thereby reducing electrolyte ionic conductivity and affecting the overall battery performance.

4. Conclusions

The recent development of electric vertical take-off and landing aircraft (eVTOL) shows promising potential to reduce emissions in the aviation sector. Use cases for this technology span from urban air taxis to agriculture and emergency medical vehicles [6]. However, the successful deployment of eVTOLs strongly depends on overcoming significant challenges in battery technology. This is due to the high energy demands for eVTOL flight, which requires batteries with gravimetric energy and power densities beyond those of most currently available energy storage systems. Additionally, the safety concerns associated with existing high-energy batteries further complicate their suitability for flight operation. Therefore, the development of safe, high-energy and -power batteries is crucial to achieve the required high performance and enable eVTOL flight. However, the absence of clear guidelines specifying battery requirements for eVTOLs poses significant challenges in selecting suitable battery chemistries. This issue is additionally exacerbated by the lack of comprehensive official standards and experimental data from OEMs.

To address this uncertainty, this paper employs analytical models and available data from real eVTOL aircrafts to determine the battery requirements in terms of gravimetric energy density and power density for eVTOL operation. Additionally, currently available battery technologies are benchmarked against these requirements, identifying nickel-based chemistries (such as NMC and NCA) as the most suitable candidates for eVTOL application. To account for the inherent differences among battery cells with the same chemistry, 300 commercial cells are analyzed from a comprehensive database, selecting the Molicel INR21700-P45B cell as the most suitable to enable eVTOL flight. A similar benchmark analysis is also performed for emerging battery chemistries, showing that solid-state batteries (SSBs) with sulfide electrolytes and silicon-based anodes (SiSu) are the most promising for enhancing the performance and safety of eVTOLs.

The suitability of these cells is verified via a simulation model designed to estimate parameters such as the battery state of charge (SoC), discharge current, and voltage. Simulations are carried out by using both the Molicel INR21700-P45B cell and a custom SiSu cell for a representative 12-min flight with two commercial eVTOL models, namely the Volocopter VoloCity and the Archer Midnight. The results indicate that the Molicel INR21700-P45B cell is only marginally adequate for high-payload, high-velocity scenarios, as its SoC lies slightly below the safety limit of 30% at the end of flight. The SiSu cell shows a much better performance, with an SoC at the end of flight of 64.9% for the Volocopter VoloCity and 64.8% for the Archer Midnight. This highlights the potential held by solid state batteries to significantly improve the performance of eVTOLs towards commercial applications. The results outlined in this paper can assist manufacturers in making informed decisions on battery selection for eVTOL development, as they highlight the limitations of current state-of-the-art battery technology and emphasize the need for the development and integration of more advanced and powerful battery technologies in future eVTOL designs.

As part of future work, the battery’s thermal properties will be incorporated into the simulation model to better capture their impact on the performance and safety of eVTOLs. Additionally, the benchmark analysis will be extended by considering additional parameters, such as the charging C-rate and cycle life, broadening the scope to identify the most economically suitable battery for eVTOL application. Finally, economic factors, including production and operational costs, as well as manufacturing and technological challenges and environmental impacts, will be incorporated to expand the analysis and offer a more comprehensive assessment of the adoption potential of specific battery technologies for eVTOLs.