Improvements in electric vehicle battery technology influence vehicle lightweighting and material substitution decisions

Joshua Thomas JamesonBurda, Elizabeth A.Moorea, HeshamEzzatbRandolphKirchainaRichardRotha
a Materials Systems Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Ave, E19-695, Cambridge, MA 02139, United States
b WorldAuto Steel/American Iron and Steel Institute, 2000 Town Center, Suite 320, Southfield, MI 48075, United States

Highlights

  • Global demand for and adoption of battery electric vehicles is on the rise.
  • To achieve increased driving range, there is increased interest in lightweighting.
  • Increased battery energy density and motor improvements can lower costs.
  • As these costs decline, the need for high cost lightweight materials will diminish.
  • Cost tradeoffs and technological advances can impact decision-making.

Abstract

Demand for battery electric vehicles (BEVs) has grown over the past decade as a result of climate action targets and energy policies globally. To improve driving range and minimize battery costs, BEV manufacturers have adopted lightweight materials with the objective of reducing energy requirements and enabling the use of smaller, less expensive batteries. However, improvements in battery energy density and electric motor technologies have enhanced vehicle performance and lowered costs independently. Thus, the need for expensive lightweight materials for mass savings could diminish as these technologies rapidly advance. This study evaluates lightweight material substitution cost tradeoffs and their changes over time for an advanced high strength steel and aluminum BEV design. Process-based cost modeling methods assess cost tradeoffs for body and closures and mass scaling estimations inform costs in the battery and motor, chassis, and other vehicle systems. Under current conditions, a steel design costs $595 less per vehicle than aluminum, where steel’s cost advantage is in body and closures manufacturing and aluminum’s advantage is in battery, motor, and chassis manufacturing cost. As lightweighting advantages of battery and motor costs decline over time, the cost gap grows wider, with a $743 per vehicle cost advantage for steel. These results underscore the importance of accounting for technological advancements and learning when projecting BEV costs. This material substitution decision ultimately has implications for energy systems and long-term profitability of BEV business models. As BEV performance and costs improve, there will be an increase in demand for BEVs, electricity, and charging infrastructure.

Keywords

Electric vehicles, Lithium-ion battery, Air cooling, Battery thermal management system, Review

Korea

배터리 전기 자동차 (BEV)에 대한 수요는 전 세계적으로 기후 행동 목표와 에너지 정책의 결과로 지난 10 년 동안 증가했습니다. 주행 거리를 개선하고 배터리 비용을 최소화하기 위해 BEV 제조업체는 에너지 요구 사항을 줄이고 더 작고 저렴한 배터리를 사용할 수 있도록 경량 소재를 채택했습니다. 그러나 배터리 에너지 밀도와 전기 모터 기술의 개선으로 차량 성능이 향상되고 비용이 독립적으로 절감되었습니다. 따라서 대량 절약을 위한 고가의 경량 재료에 대한 필요성은 이러한 기술이 빠르게 발전함에 따라 감소 할 수 있습니다. 이 연구는 고급 고강도 강철 및 알루미늄 BEV 설계에 대한 경량 재료 대체 비용 절충과 시간 경과에 따른 변화를 평가합니다. 프로세스 기반 비용 모델링 방법은 차체 및 폐쇄에 대한 비용 절충을 평가하고 질량 확장 추정은 배터리 및 모터, 섀시 및 기타 차량 시스템의 비용을 알려줍니다. 현재 상황에서 강철 디자인은 알루미늄보다 차량 당 595 달러 더 저렴합니다. 강철의 비용 이점은 차체 및 폐쇄 제조에 있고 알루미늄의 이점은 배터리, 모터 및 섀시 제조 비용에 있습니다. 배터리 및 모터 비용의 경량화 이점이 시간이 지남에 따라 감소함에 따라 비용 격차는 더 넓어지고 강철의 경우 차량 당 비용 이점이 $ 743입니다. 이러한 결과는 BEV 비용을 예측할 때 기술 발전과 학습에 대한 설명의 중요성을 강조합니다. 이 물질 대체 결정은 궁극적으로 에너지 시스템과 BEV 비즈니스 모델의 장기적인 수익성에 영향을 미칩니다.

Graphical abstract

Introduction


  1. The adoption of electric vehicles (EVs) is growing, with the global
    stock of EVs exceeding 7 million in 2019. Under future market scenarios,
    the stock of EVs could rapidly grow to 130 million EVs in 2030 [1] given:
    1) efforts to mitigate greenhouse gas (GHG) emissions [2], 2) increased
    accessibility to EVs through policy tools and climate action targets [1,3]
    and 3) falling costs of ownership [4,5]. Continued battery electric
Fig. 1. Detailed information flow chart for body, closure, and paint cost model (green), mass-scaling for battery, motor, and chassis systems (purple), and rest of vehicle cost estimation (purple).
Fig. 1. Detailed information flow chart for body, closure, and paint cost model (green), mass-scaling for battery, motor, and chassis systems (purple), and rest of vehicle cost estimation (purple).
Fig. 2. Process-based cost modeling structure for the estimation of parts manufacturing costs where process specific information (orange) informs the time, energy, labor, and equipment requirements for each part.
Fig. 2. Process-based cost modeling structure for the estimation of parts manufacturing costs where process specific information (orange) informs the time, energy, labor, and equipment requirements for each part.
Fig. 3. Process-based cost modeling structure for the estimation of assembly costs where process specific information (orange) informs the time, energy, labor, and equipment requirements for each part.
Fig. 3. Process-based cost modeling structure for the estimation of assembly costs where process specific information (orange) informs the time, energy, labor, and equipment requirements for each part.
Fig. 4. Material breakdown in the FSV advanced high strength steel vehicle body design. The vehicle is comprised of 161 parts weighing 249.7 kg and includes mild steel, Bake-Hardenable (BH), High Strength Low Alloy (HSLA), Transformation Induced Plasticity (TRIP), Dual-Phase (DP), Complex-Phase (CP), Martensitic (MS), Twinning Inducted Plasticity (TWIP), and Hot-Formed (HF) steel. The cost of purchasing material and manufacturing parts is approximately $923.
Fig. 4. Material breakdown in the FSV advanced high strength steel vehicle body design. The vehicle is comprised of 161 parts weighing 249.7 kg and includes mild steel, Bake-Hardenable (BH), High Strength Low Alloy (HSLA), Transformation Induced Plasticity (TRIP), Dual-Phase (DP), Complex-Phase (CP), Martensitic (MS), Twinning Inducted Plasticity (TWIP), and Hot-Formed (HF) steel. The cost of purchasing material and manufacturing parts is approximately $923.
Fig. 5. Battery cost model combines energy and mass scaling algorithms with existing Argonne National Lab BatPac model to estimate battery costs for the AHSS and Al lightweight design.
Fig. 5. Battery cost model combines energy and mass scaling algorithms with existing Argonne National Lab BatPac model to estimate battery costs for the AHSS and Al lightweight design.
Fig. 6. Battery pack cost for different battery chemistries as a function of battery capacity (kWh), where the red line represents the aluminum design and the blue line represents the steel design.
Fig. 6. Battery pack cost for different battery chemistries as a function of battery capacity (kWh), where the red line represents the aluminum design and the blue line represents the steel design.
Fig. 7. Cost and mass scaling for the motor subsystems to estimate motor costs for the AHSS and Al lightweight design.
Fig. 7. Cost and mass scaling for the motor subsystems to estimate motor costs for the AHSS and Al lightweight design.
Fig. 8. Vehicle mass by component for the future steel vehicle (FSV) and aluminum comparator design.
Fig. 8. Vehicle mass by component for the future steel vehicle (FSV) and aluminum comparator design.
Fig. 9. Body and closure cost by material, manufacturing, assembly, and paint system for Vehicle 1, the future steel vehicle (FSV) and Vehicle 2, the aluminum comparator design.
Fig. 9. Body and closure cost by material, manufacturing, assembly, and paint system for Vehicle 1, the future steel vehicle (FSV) and Vehicle 2, the aluminum comparator design.
Fig. 10. Full vehicle manufacturing costs compared for the FSV, Vehicle 1 and the aluminum-intensive vehicle, Vehicle 2.
Fig. 10. Full vehicle manufacturing costs compared for the FSV, Vehicle 1 and the aluminum-intensive vehicle, Vehicle 2.

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