Our chosen Technology is that of electricity storage via battery for the purpose of vehicle mobility. We will refer to it within our descriptions as "battery" This is a level 3 technology. It serves the major subsystems found in electric vehicles
The working principle and architecture of an electrical battery are depicted in the below.
Figure 1.1: Lithium-Ion Battery (Technology ID# 1.000) working principle and architecture
Figure 2.1: DSM of the battery and technology hierarchy
Our technology of interest is identified in the DSM above with green highlighting. it is portrayed in the context of the consuming technology of interest, electric vehicles, where we identified the typical consuming technology systems for reference. The diagram on the right is a dependency tree that has been extracted from the DSM. The battery storage technology consumes technology related to battery chemistry, including cathode, anode, catalyst, and semi-permeable membrane technologies. Battery technology also consumes technology related to the design of the shipping, manufacturing, material supply chain, and internal circuitry technologies
We provide an Object-Process-Diagram (OPD) of the Battery technology in the figure below. This diagrams captures the main object of the technology (Battery), the value-generating processes and different instruments associated with their characterization by Figures of Merit (FoM).
Figure 3.1: OPD representation of a battery pack
An Object-Process-Language (OPL) description of the roadmap scope is auto-generated and given in OPL_Battery. It reflects the same content as the previous figure, but in a formal natural language.
The first two (shown in bold) are mainly used to assess the battery itself. These FOMs are often used for evaluation of the battery performance. The other rows represent additional FOMs for a rechargeable battery.
Note: basic reminders (as we rediscovered them) about the units and relationships:
Table 4.1: Alignment to Strategic Drivers
We position ourselves as a battery supplier of a mid-market, non dominant electric vehicle. We explore the performance of our competitors in 2016-2019 across our two fundamental FOMs of our battery pack: Energy intensity (Wh/kg) and Cost Intensity of energy ($/kWh). The graph provided below is based on this benchmark of battery packs performance used in different medium-size electric vehicles on the market.
Figure 5.1: Benchmark of performance of battery packs for various mid-size electric vehicles, in 2016-2019
Tesla has stated that their current cathode technology in production is a Nickel-Cobalt-Aluminum (NCA) mixture and they state that the typical competition battery is utilizing Nickel-Manganese-Cobalt (NMC). They have also stated that Cobalt prices are the key driver of cost with the battery technologies overall. They have stated that they are experimenting with reduced amounts of Cobalt as a pathway to reduced costs. It has also been reported that Chinese battery manufacturer CATL is tranistioning from a 20% Cobalt formulation to a 10% Cobalt formulation in 2019.
In order to assess the feasibility of technical targets, at the level of the battery roadmap, we develop a technical model. The purpose of this model is to evaluate the sensitivity of each technology development and its feasibility.As a first step, we develop a morphological matrix that shows architectural decisions for the next Lithium-Ion battery.
Figure 6.1: Morphological matrix, Lithium-ion secondary battery cell
The morphological matrix for the battery technology is provided above illustrating the current known materials and methods for several of the key design decisions. The projects stemming from this roadmap could include these options or could identify additional options for exploration.
The results of the sensitivity analysis are shown in the figure below and summarized the result in a table below:
Figure 6.2: Sensitivity_analysis_for_specific_energy
Table 6.1: Summary of Sensitivity_analysis
To check the feasibility if which technology development can achieve our objective energy density (350 Wh/kg) we analyze the parameters of ΔE, qc and qa.
Figure 6.3: Feasibility Analysis
From the feasibility analysis, we can say if the ΔE is less than 5V (usual ΔE is about 3.6V like a reference), it is difficult to achieve the target D (350 Wh/kg) only by developing an anode. Also, according to equation②, the less molecular weight (M) contributes to the higher cathode capacity. However, to improve the cathode capacity over 400 [Ah/kg], the molecular weight of the cathode material must be less than 67 [g/mol] even if the value of "a" ideally equals to 1. This result definitely limits the design of the cathode material. Therefore, our suggestion from the technical perspective is to develop not only cathode but also anode to increase their capacity by considering their combination for high ΔE.
Note: As a historical data, the more energy density shows the less lifecycle shown in the graph below. Interestingly, these two parameters look like a tradeoff, so we have to evaluate the electrode materials in terms of lifecycle even if these shows desired performances (high ΔE and capacity).
Figure 6.4: Tradespace clustered by architectural decision about the cathode, Lithium-ion secondary battery cell
A detailed review is provided in Li-Ion Key publications and patents.
Figure 8.1: Battery value chain. We assume we are a supplier of battery packs for Electric Vehicles. Image from [1]: Schmuch, R., Wagner, R., Hörpel, G., Placke, T. & Winter, M. Performance and cost of materials for lithium-based rechargeable automotive batteries. Nat. Energy 3, 267–278 (2018).
We are an existing battery supplier targeting electric vehicle market, with a product equivalent today (2020) with the performance of the "Renault Zoe" battery, i.e. we are not market leader, we have today a 5% market share on the global electric vehicles market [2] with a market strategy targeting increasing our market share to 10% of the electric vehicles market worldwide, equivalent of today''s Nissan Leaf. As a reference, Tesla Model 3 captures the biggest market share with 19% of electric vehicles sales worldwide [2].
As a general context, we evaluate that the sales of electric vehicles, which today represent less than 1% of the number of cars sold worldwide [3], will exponentially increase in the next decade, from 0.8 million today up to 25 millions or more of EV vehicles sold in 2030 [4]. We conservatively assume that the number of electric vehicles sold per year will be annually multiplied by 1.4, reaching 23 million in 2030.
In this context, we carry on a baseline NPV analysis with a 10-year period of observation. We assume that our product is reaching and maintaining a share of 5% of the EV Market based ("free-riding" on the R&D, no additional investment) with a battery pack cost of 160$/kWh [5, 6], and an energy capacity per battery of 55 kWh (with a density of 130 Wh/kg). We use a discount rate of 15%. We include upfront expanses to upgrade manufacturing facilities, and non-recurring cost of the product development which include R&D expenditures. We allow 2 years of project development and start the sales in 2023 with a ramp-up to our full estimated market share from 2023 to 2025.
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