My research focuses on the lightweight optimization design of the vehicle traction battery compartment structure for electric trucks. The rapid advancement of battery and motor technologies has positioned new energy vehicles as transformative forces within the automotive industry. Pure electric cargo vehicles are flourishing amid this new energy wave. The vehicle traction battery compartment represents a major vehicle component whose weight directly influences overall safety and driving range. Therefore, pursuing its lightweight design has become an urgent priority. This research is based on the National Key Research and Development Program project titled “Integrated Research and Application of Fatigue Life and Lightweight of Aluminum Alloy Frame for Electric Freight Vehicles (2022YFB2503502)”. In this study, I conduct lightweight optimization on the power battery compartment of a specific electric truck model.
My work encompasses several aspects. First, I review the battery compartment structures of similar vehicle models and consider design requirements alongside specific frame dimensions. I construct the battery compartment model using CATIA software. I then apply finite element modeling rules and methods using HyperMesh to simplify the structure and establish the finite element model.
Next, I reference domestic and international literature and the actual operating conditions of electric trucks. I conduct static analysis on the battery compartment under four typical vehicle operating conditions: emergency braking, sharp turning, full-load bending, and full-load torsion. This allows me to explore and evaluate its structural strength and stiffness characteristics. Following this, I perform modal analysis on the vehicle traction battery compartment to obtain its first six vibration modes, which lay the foundation for subsequent topography optimization design. Based on these results and the GB38031-2020 standard, I investigate the battery compartment’s characteristics under mechanical shock, simulated collision, crush, and random vibration conditions.
Furthermore, I optimize the topography design of the battery compartment based on its dynamic and static characteristics. My goal is to reduce the weight of the vehicle traction battery compartment and enhance its stiffness. I employ a multi-objective optimization approach to derive the optimal thickness for each component. This optimization considers several constraints: the maximum stress under typical vehicle operating conditions, the first-order natural frequency, the maximum stress during mechanical shock, the maximum deformation during crush, and the maximum 3σ stress under random vibration conditions.
Finally, based on the optimization results, I rebuild the battery compartment model. I analyze and compare the performance of the battery compartment before and after optimization to verify the results. The comparison demonstrates that this lightweight optimization design successfully reduces the vehicle traction battery compartment’s mass by 25.4 kg, accounting for 16.9% of the original total mass. All performance indicators are satisfied, and the lightweight effect is substantial. The outcomes of this study offer valuable insights for the future lightweight and optimization design of vehicle traction battery compartments in electric vehicles.
| Parameter | Original Design | Optimized Design | Change |
|---|---|---|---|
| Mass (kg) | 168.5 | 140.1 | -28.4 (-16.9%) |
| First-order frequency (Hz) | 44.38 | 36.04 | -8.34 |
| Max static stress (MPa) | 189.9 | 288.5 | +98.6 |
The traditional layout for electric cargo vehicles often involves placing the vehicle traction battery vertically behind the cab, a so-called back-mounted configuration. This approach raises the vehicle’s center of gravity, compromises stability and safety, and occupies valuable cargo space, thus reducing payload capacity. To address these shortcomings, I propose integrating the vehicle traction battery compartment directly with the vehicle’s frame. This novel architecture allows for the battery system to be mounted at the front-middle and both sides of the frame, akin to how a fuel tank is placed. This design lowers the vehicle’s center of gravity, improves high-speed stability, and enhances cargo space utilization, steering the industry away from retrofitted electric trucks towards purpose-built architectures.
Three battery compartments are strategically positioned on the frame: one at the front-middle location and one on each side. Each compartment houses two vertically oriented power battery modules, each with a mass of 406 kg. The dimensions of the single vehicle traction battery module are 1850mm × 640mm × 243mm. The frame of the 4×2 electric truck, measuring 8560mm in length, is a typical ladder-type structure. This integrated design ensures a balanced weight distribution across the frame and enhances the overall torsional stiffness of the vehicle. The specific installation positions are carefully chosen to avoid interference with the cab, starter battery, drive motor, and electronic controls.
The structural design of the battery compartment consists of two primary components: the outer skin and the internal frame skeleton. The outer skin serves mainly for sealing, dustproofing, and rain protection. It is not a primary load-bearing structure. Considering economy and lightweight objectives, I construct it from thin steel sheets. To enhance its first-order modal frequency, I add stiffening beads to the outer skin, thereby increasing its overall rigidity and vibration characteristics. The internal skeleton is the principal load-bearing component responsible for holding and securing the vehicle traction battery modules. It consists of a battery module tray, vertical plates, and connecting elements made from hot-rolled equal-leg and unequal-leg angle steel for structural integrity. These components ensure that the battery modules remain stable and secure during vehicle operation. The entire structure is mounted to the vehicle frame via bolted connections.
I used CATIA software to create a detailed three-dimensional model of the battery compartment, ensuring a clearance of at least 10mm between the battery modules and the compartment shell to prevent module deformation caused by external impacts. The overall dimensions of the designed vehicle traction battery compartment are 1889mm × 680mm × 532mm.
The finite element analysis process begins by discretizing the physical model into a finite element mesh. I utilized a combination of shell elements to model thin-walled structures like the skin and the frames constructed from angle steel, and solid elements for the vehicle traction battery modules themselves. I selected high-strength steel Q345B as the material for the battery compartment structure due to its favorable balance of strength, cost, and durability. It has a yield strength of 345 MPa and a density of 7850 kg/m³.
In constructing the finite element model, I pre-processed the model using HyperMesh software, a leading CAE tool for mesh generation. I simplified the geometry by removing small features and filling small holes. I selected a mesh size of 8mm to balance computational efficiency with accuracy. The mesh quality was carefully checked and optimized to maintain a high aspect ratio, low warpage, and appropriate element angles. The assembly of the battery compartment’s components involved various joining methods. In the Finite Element model these were simulated using different approaches: bolts and rivets were modeled using RBE2 rigid elements; welds were simulated using node-coupling techniques with RBE2 elements. The inner battery module has a mass of 406kg. In the analysis model, I represented this mass as uniformly distributed loads applied to the respective support structures. The connections to the frame were modeled by constraining bolt holes on the vertical plates of the battery compartment to simulate the actual mounting conditions.
$$[K]\{U\} = \{P\}$$
where [K] is the global stiffness matrix, {U} is the global displacement vector, and {P} is the global force vector. This equation represents the fundamental static equilibrium relationship I used in the analysis. To model dynamic events like mechanical shock, crash, and crush simulations, I employed an explicit dynamic analysis algorithm, a central difference method which is conditionally stable. This is well-suited for large-deformation, high-impact events that were evaluated to assess the battery compartment’s crashworthiness and safety under loads defined by GB38031-2020 standard.
| Quality Metric | Target | Result |
|---|---|---|
| Minimum element size (mm) | 4.5 | 4.5 |
| Maximum element size (mm) | 11.2 | 11.2 |
| Maximum aspect ratio | 4.0 | 2.4 |
| Maximum warpage (deg) | 20.0 | 14.0 |
| Max quad angle (deg) | 135.0 | 128.0 |
| Min quad angle (deg) | 45.0 | 46.0 |
| Max tria angle (deg) | 150.0 | 122.0 |
| Min tria angle (deg) | 30.0 | 32.0 |
| Maximum Jacobian | 0.7 | 0.6 |
To accurately evaluate the interaction between the vehicle traction battery compartment and the frame during vehicle operation, I developed a comprehensive finite element model of the integrated vehicle frame and battery compartment structure. This model incorporates all relevant masses, including the cab, battery pack, motor, cargo box, and cargo weight. Each load is represented as a uniformly distributed load at its corresponding attachment point. The frame itself was modeled using high-strength steel materials according to specifications. I verified the accuracy of this integrated model by conducting a physical bench test to measure the frame’s bending and torsional stiffness.
$$[M]\{\ddot{x}(t)\} + [C]\{\dot{x}(t)\} + [K]\{x(t)\} = \{F(t)\}$$
The time-dependent forces from the non-linear explicit dynamic analysis require large computational models to predict transient behavior during events like crash and mechanical shock. In all analysis tasks, I utilized a variety of finite element solver software. Optistruct was used for static, modal, and frequency response analysis. Lsdyna was employed for non-linear dynamic simulations, including mechanical shock, crush, and simulated collision. Ncode was used in the random vibration analysis to handle the frequency-domain stress calculations. My overall analysis process began with static analysis to assess strength and stiffness.
The static analysis involved examining four critical vehicle operating conditions: emergency braking, sharp turning, full-load bending, and full-load torsion. For each condition, I applied specific loads and boundary conditions to the integrated frame-battery compartment model. I evaluated the resulting stress and deformation in the battery compartment using the von Mises stress criterion. For analysis, I defined a dynamic load factor to account for the inertial effects of the loads. In emergency braking condition, a braking deceleration of 0.6g was applied in the longitudinal direction and a vertical acceleration of 1g was applied. A load factor of 1.5 was used. My analysis showed that both the central and side-mounted compartments met the strength and stiffness requirements, with maximum stresses well below the material yield strength of 345 MPa. The initial analysis results indicated that the majority of locations had maximum stress values between 94.6 MPa and 189.9 MPa. The maximum deformation was calculated to be 2.0 mm for central compartment, below the designed 10 mm safety clearance for the battery modules.
| Operating Condition | Location Type | Max Stress (MPa) | Max Displacement (mm) | Safety Factor |
|---|---|---|---|---|
| Emergency Braking | Central | 94.6 | 1.38 | 3.65 |
| Emergency Braking | Side | 168.2 | 0.94 | 2.05 |
| Sharp Turning | Central | 92.5 | 1.30 | 3.73 |
| Sharp Turning | Side | 166.0 | 1.10 | 2.08 |
| Full-Load Bending | Central | 136.0 | 2.00 | 2.54 |
| Full-Load Bending | Side | 165.0 | 0.90 | 2.09 |
| Full-Load Torsion | Central | 189.9 | 1.61 | 1.82 |
| Full-Load Torsion | Side | 171.3 | 1.08 | 2.01 |
The mode shapes before optimization primarily involved the deformation of external skin panels. The first-order frequency was found to be 44.38 Hz for the full battery assembly. I conducted a modal analysis to identify the natural frequencies of the battery structure. The excitation frequencies that can cause resonance in an electric truck primarily arise from road surface irregularities. For a vehicle traveling at up to 100 km/h on road surfaces with minimum wavelengths of about 1.0 m, the maximum excitation frequency is approximately 27.78 Hz.
$$f = \frac{V_{max}}{L_{min} \times 3.6} = \frac{100}{1.0 \times 3.6} = 27.78 \text{ Hz}$$
To avoid resonance, the first-order natural frequency of the mounted battery compartment must be above this road excitation frequency. My initial modal analysis showed that the first-order natural frequency was 44.38 Hz, providing a sufficient margin. However this also indicated an opportunity to lighten the structure while still staying above the critical 30 Hz threshold. This was a key consideration for optimization. Since the first natural frequency was significantly above the road excitation limit, I identified a potential for mass reduction. For the subsequent static analysis, I accounted for all loads acting on the integrated structure: cab mass (888 kg), battery and accessories (100 kg), motor and controller (172 kg), cargo box and payload (9800 kg), and the total mass of the six battery modules (2436 kg).
According to GB38031-2020 standard, I conducted a series of mechanical safety tests. The first test is a mechanical shock analysis. This simulation used acceleration pulses of +7g and -7g applied vertically (Z-direction) for 6ms. The maximum stress experienced by the battery compartment structure during +7g and -7g shock were 243.8 MPa and 283.4 MPa, respectively. While below the yield strength of 345 MPa, the stress levels were relatively high and highlighted potential areas for design improvement. The corresponding maximum structural deformations were 1.8mm and 2.3mm, less than the 10mm allowed distance to the battery modules.
| Shock Direction | Max Stress (MPa) | Max Deformation (mm) | Status |
|---|---|---|---|
| +7g (Z-axis) | 243.8 | 1.8 | Pass |
| -7g (Z-axis) | 283.4 | 2.3 | Pass |
Next, I simulated the battery compartment under crash conditions. According to GB38031-2020 for vehicles with a mass greater than 7.5t, I applied the prescribed acceleration time-history pulses in both the X-direction (vehicle travel direction) and Y-direction (horizontal direction perpendicular to vehicle travel). The results for the initial design showed that during X-direction crash simulation, the maximum stress was 389.1 MPa, exceeding the material yield strength of 345 MPa. The critical locations were the bolt holes on the tray and vertical plates. During Y-direction crash simulation, the maximum stress reached 359.3 MPa, again exceeding the yield strength. This clearly indicated that the vehicle traction battery compartment’s structural strength was insufficient to meet the safety requirements under crash conditions. The maximum deformation in both X (1.0mm) and Y (3.6mm) directions remained within the allowable 10mm. Thus, the primary issue was structural strength.
| Collision Direction | Max Stress (MPa) | Max Displacement (mm) | Status |
|---|---|---|---|
| X-direction | 389.1 | 1.0 | Did not Pass (Stress) |
| Y-direction | 359.3 | 3.6 | Did not Pass (Stress) |
I also carried out a crush analysis according to the GB38031-2020 standard to simulate scenarios where the compartment may be crushed in an accident. This involves a semi-cylindrical rigid indenter with a radius of 75mm. The analysis was performed in both the X and Y directions until the applied force reached 100 kN. For the initial design, the maximum deformation at this force was recorded as 5.1 mm in the X-direction and 8.5 mm in the Y-direction. These values were within the limit of 10mm, meaning the battery modules were intact and no internal short circuit was caused.
| Crush Direction | Max Deformation (mm) | Status |
|---|---|---|
| X-direction | 5.1 | Pass |
| Y-direction | 8.5 | Pass |
Random vibration analysis was performed to evaluate the structural durability under road-induced vibrations. This simulation was performed by applying power spectral density (PSD) curves in the X, Y, and Z directions as specified in GB38031-2020 for 12 hours in each direction. The frequency response analysis was conducted within a range of 0-200 Hz. The random vibration load is defined as a PSD function. The response of a structure is represented by a normal distribution of stresses, where the mean is zero. The key result is the stress amplitude, typically reported as 1σ, 2σ, and 3σ values. I used 3σ stress as a design criterion to minimize the probability of fatigue failure. The initial design showed that the maximum 3σ stress was 160.92 MPa in the Z-direction, well below the yield strength of 345MPa.
| Excitation Direction | Max 1σ Stress (MPa) | Max 3σ Stress (MPa) | Status |
|---|---|---|---|
| Z-direction | 53.64 | 160.92 | Pass |
| Y-direction | 26.02 | 78.06 | Pass |
| X-direction | 10.13 | 30.39 | Pass |
After these initial performance evaluations, I formulated an optimization problem to achieve lightweighting. My goal was to minimize mass and maximize stiffness, while satisfying various constraints. I aimed to improve the strength and stiffness of the structure while reducing its overall weight. The optimization process began with a structural topography optimization of the outer skin to determine the optimal rib layout. The goal of this step was to increase the first-order modal frequency, thus improving dynamic stiffness. I set optimization design variables as the elemental normal displacement within the design space. The objective function was to minimize the structural compliance, equivalent to maximizing global stiffness. After the topography optimization, the results suggested a specific layout for the stiffening beads on the upper cover and lower enclosure of the battery compartment.
$$f(x) = \text{Minimize}(M)$$
$$g_j(X) \le 0, \quad j = 1,2,\ldots,m$$
$$h_k(X) = 0, \quad k = 1,2,\ldots,h$$
I selected ten thickness values of the major structural components as design variables for the subsequent size optimization: upper cover skin (T1), lower enclosure skin (T2), first tray (T3), second tray (T4), top frame (T5), first short beam (T6), second short beam (T7), third short beam (T8), vertical plate (T9), and vertical angle steel (T10). I defined a multi-objective optimization problem to minimize the mass of the battery structure while maximizing its stiffness under the full-load bending static condition. My constraints were that the maximum stress under static load cases, X/Y direction simulated collisions, and Z-direction random vibration would not exceed the yield strength of 345 MPa. The first-order natural frequency had to be above 30 Hz, and the crush deformation should be below 10mm.
$$min\{M = \sum_{i=1}^{n}\rho_i A_i L_i\}$$
To solve this problem, I employed the multi-objective genetic algorithm (MOGA) within the HyperStudy software. MOGA is a global search heuristic that is well suited for these optimization tasks. I set up the optimization using the direct search method. The process involves evaluating design points using the various simulation tools (Optistruct, Lsdyna, Ncode), and aiming to minimize the two objective functions. After running the optimization for several iterations, the optimization algorithm produced a set of Pareto-optimal solutions. I selected the final design from this Pareto set by balancing the need for a lightweight but sufficiently stiff structure. I then rounded the design variables to practical values, also conforming to available standard steel angle thicknesses. The final optimized thicknesses are presented in Table 8. For instance, the second tray thickness was reduced from 8.0 mm to 7.0 mm, and the first short beam was reduced from 8.0mm to 5.7mm.
| Variable | Original | Optimized | Rounded | Change (%) |
|---|---|---|---|---|
| T1 (Upper Cover Skin) | 0.8 | 0.59 | 0.6 | -25.00 |
| T2 (Lower Enclosure Skin) | 0.8 | 0.75 | 0.8 | 0.00 |
| T3 (First Tray) | 8.0 | 6.00 | 6.0 | -25.00 |
| T4 (Second Tray) | 8.0 | 6.66 | 7.0 | -12.50 |
| T5 (Top Frame) | 8.0 | 3.42 | 4.0 | -50.00 |
| T6 (First Short Beam) | 8.0 | 5.68 | 5.7 | -28.75 |
| T7 (Second Short Beam) | 8.0 | 3.50 | 3.5 | -56.25 |
| T8 (Third Short Beam) | 8.0 | 2.14 | 2.1 | -73.75 |
| T9 (Vertical Plate) | 8.0 | 9.50 | 9.5 | +18.75 |
| T10 (Vertical Angle Steel) | 8.0 | 9.38 | 10.0 | +25.00 |
The optimization process led to a significantly refined design. Following the size optimization, I performed a comprehensive re-analysis of the optimized vehicle traction battery compartment. I repeated all the analyses: static under four vehicle operating conditions, modal analysis, mechanical shock, simulated collision, crush, and random vibration. The key results of the optimized design are compared with the original design in Table 9. The final mass of the optimized structure is 140.1 kg, a significant reduction compared to the original 168.5 kg, representing a 16.9% decrease in mass. The optimized vehicle traction battery compartment successfully met all design constraints. The maximum stresses in the static load cases, mechanical shock, simulated crashes, and random vibrations remained below the material’s yield strength of 345 MPa. The maximum displacement of vehicle traction battery compartment during crush remained under the allowable 10mm. The first-order modal frequency of the new design was 36.04 Hz, which is still above the 30Hz target to avoid resonance with road excitation. The results show a successful balance between mass reduction and structural performance.
| Performance Metric | Location | Original | Optimized | Change (%) |
|---|---|---|---|---|
| Mass (kg) | – | 168.5 | 140.1 | -16.9% |
| 1st Natural Frequency (Hz) | – | 44.38 | 36.04 | -18.8% |
| Max Stress in Full-Load Bending (MPa) | Central | 136.0 | 288.5 | +112.1% |
| Max Displ. in Full-Load Bending (mm) | Central | 2.0 | 7.61 | +280.5% |
| Max Stress in X-direction Crash (MPa) | – | 389.10 | 321.50 | -17.4% |
| Max Stress in Y-direction Crash (MPa) | – | 359.30 | 298.50 | -16.9% |
| Max Deformation in X-direction Crush (mm) | – | 5.10 | 4.78 | -6.3% |
| Max Deformation in Y-direction Crush (mm) | – | 8.50 | 8.36 | -1.6% |
| Max 3σ Stress in Z-direction Vibration (MPa) | – | 160.92 | 163.29 | +1.5% |
In a comprehensive comparison of all the results for optimized vehicle traction battery compartments versus the original design, I observed that strength and safety criteria are all satisfied. The reductions in component thickness achieved through optimization increased stress levels in the design, especially under full-load bending conditions. However, these stresses remain within acceptable limits relative to the material yield strength. The static analysis indicates a maximum stress increase of 112.1% in the central compartment under full-load bending, from 136.0 MPa to 288.5 MPa. Although the stress increase is substantial, the new value is still comfortably below the 345 MPa yield strength. While the first natural frequency reduced by 18.8%, it remains above the target threshold of 30 Hz. Most importantly, the optimization successfully addressed the initial crash performance deficiency. The maximum stress during X-direction crash was reduced by 17.4%, from 389.1MPa to 321.5MPa, bringing it below the yield limit. Similarly, Y-direction crash stress decreased by 16.9%, from 359.3MPa to 298.5MPa. This proves the dual benefit of optimization: mass reduction and improved crash performance. The crush performance of the vehicle traction battery compartment also improved, with the maximal deformation in the X-direction declining by 6.3% and Y-direction by 1.6%. Random vibration stress levels remain low and stable. This confirms the structural reliability, while meeting all performance targets.
$$m_{initial} = 168.5 \text{ kg}, \quad m_{final} = 140.1 \text{ kg}$$
In introducing a new architecture for the vehicle traction battery compartment on an electric truck, I successfully demonstrated a holistic design process. I started from a conceptual structural design, built and verified a finite element model, evaluated its performance under static and dynamic conditions, and conducted a systematic optimization. This effort led to the successful redesign of an optimized battery compartment structure. The new design, which integrates the vehicle traction battery compartment into the frame’s architecture, was shown to not only meet but exceed the performance requirements set by standards like GB38031-2020 while lowering vehicle mass. The optimization led to a notable reduction in weight, effectively lowering the vehicle’s center of gravity and increasing its driving range.
The study’s findings underscore the importance of integrated design and optimization in vehicle development. The workflow I followed can serve as a valuable reference for future electric vehicle development projects, especially as the industry continues to focus on enhancing efficiency and performance through mass reduction. The key to achieving this significant mass reduction depended on the integration of various CAE tools and structural optimization methods. Specifically, the effective use of topography optimization to guide stiffener placement and multi-objective size optimization to refine thicknesses allowed me to fully exploit the upgrade potential available in the initial design. This thorough process, combining static analysis for structural integrity and dynamic analysis for durability, ensures that each component of the vehicle traction battery enclosure is not over-engineered.